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capon-0.0.8


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توضیحات

Capital Market in Python
ویژگی مقدار
سیستم عامل -
نام فایل capon-0.0.8
نام capon
نسخه کتابخانه 0.0.8
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Eyal Gal
ایمیل نویسنده eyalgl@gmail.com
آدرس صفحه اصلی https://github.com/gialdetti/capon/
آدرس اینترنتی https://pypi.org/project/capon/
مجوز -
# capon **Cap**ital Market in **P**yth**on** | Author | Version | Demo | | :----------: | :--------------------------------------: | :--------------------------------------: | | Gialdetti | [![PyPI](https://img.shields.io/pypi/v/capon.svg)](https://pypi.org/project/capon/) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/gialdetti/capon/master?filepath=examples%2Fmonitoring%2Fmy_portfolio_performance.ipynb) | | `capon` is a python package for easily obtaining and analyzing real-time stock data. It provides extended datasets of stock metadata and features. In addition, it offers simple APIs for tracking your personal stock portfolios and their live status. ## Installation ### Install latest release version via [pip](https://pip.pypa.io/en/stable/quickstart/) ```bash $ pip install capon ``` ### Install latest development version ```bash $ pip install git+https://github.com/gialdetti/capon.git ``` or ```bash $ git clone https://github.com/gialdetti/capon.git $ cd capon $ python setup.py install ``` ## A simple example Get the historical stock price of AMD, and plot it. ```python import capon amd = capon.stock('AMD', range='ytd') ``` ![](./examples/images/themes/capon/readme_amd_dataframe.png) The historical data is given as a standard [pandas](https://pandas.pydata.org/) dataframe. This allows a fast and powerful data analysis, manipulation and visualization. For instance, ```python amd.plot(x='timestamp', y='adjclose') ``` ![Alt text](./examples/images/themes/capon/readme_amd.png) ## My portfolio example Track your personal stock portfolio with real-time data. a) Define my holdings ```python from capon import Portfolio, Lot my_portfolio = Portfolio([ Lot('2020-03-20', 'AMZN', 2, 1888.86), Lot('2020-03-20', 'TSLA', 8, 451.40), Lot('2020-03-23', 'GOOGL', 3, 1037.89), Lot('2020-03-23', 'AMC', 1041, 2.88), Lot('2020-03-27', 'ZM', 20, 150.29), ]) ``` ![Alt text](./examples/images/themes/capon/readme_my_portfolio.png) b) Sync with real-time stock data to find current status ```python status = my_portfolio.status() display(status) total_cost, total_value = status.sum()[['cost', 'value']] print(f'Total cost: {total_cost:,.2f}; Market value: {total_value:,.2f}') print(f'Total gain: {total_value-total_cost:+,.2f} ({total_value/total_cost-1:+,.2%})') ``` ![Alt text](./examples/images/themes/capon/readme_my_portfolio_status.png) c) Plot it ```python from capon.visualization import plot_status plot_status(status) ``` ![Alt text](./examples/images/themes/capon/readme_my_portfolio_status_bar.png) d) Plot historical data ```python import plotly.express as px performance = my_portfolio.performance() px.line(performance, x='timestamp', y='gain_pct', color='symbol', template='capon') ``` ![Alt text](./examples/images/themes/capon/readme_my_portfolio_history.png) The full example in a live notebook is provided [below](#examples). ## Help and Support ### Examples The tutorials below aim to provide a clear and concise demonstration of some of the most important capabilities of `capon`. For instance, step-by-step guides for building and real-time monitoring of your portfolio, for fetching and analyzing stock historical data, or for using stocks metadata. To make it a bit more interesting (hopefully), each tutorial first poses a meaningful stock-market "research question". In the context of answering these questions, the tutorials demonstrate the relevant library features. | Theme | MyBinder | Colab | | ------------ | :----------: | :---: | | [My Stock Portfolio Performance](https://nbviewer.jupyter.org/github/gialdetti/capon/blob/master/examples/monitoring/my_portfolio_performance.ipynb) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/gialdetti/capon/master?filepath=examples/monitoring/my_portfolio_performance.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gialdetti/capon/blob/master/examples/monitoring/my_portfolio_performance.ipynb) | | [Stock Market Crash and Rebound Amid Coronavirus](https://nbviewer.jupyter.org/github/gialdetti/capon/blob/master/examples/market_analysis/stock_indexes.ipynb) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/gialdetti/capon/master?filepath=examples/market_analysis/stock_indexes.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gialdetti/capon/blob/master/examples/market_analysis/stock_indexes.ipynb) | | [Analyzing the Sector-level Crash and Rebound](https://nbviewer.jupyter.org/github/gialdetti/capon/blob/master/examples/market_analysis/sector_crash_and_rebound.ipynb) | [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/gialdetti/capon/master?filepath=examples/market_analysis/sector_crash_and_rebound.ipynb) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/gialdetti/capon/blob/master/examples/market_analysis/sector_crash_and_rebound.ipynb) | ## Testing After cloning and installing the development version, you can launch the test suite: ```bash $ pytest ```


نیازمندی

مقدار نام
>=1.17.3 numpy
>=1.0.3 pandas
>=2.22.0 requests
>=4.7.1 plotly
- tqdm


نحوه نصب


نصب پکیج whl capon-0.0.8:

    pip install capon-0.0.8.whl


نصب پکیج tar.gz capon-0.0.8:

    pip install capon-0.0.8.tar.gz