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* move old example notebooks to v3 folder, update loadHistoricalPriceData and add findSymbols * Create README.md * Update README.md * Update README.md * Update README.md * Vertical diagram instead * important classes * core dependencies * folder structure * devtools * swap order * fix github pages deploy issue * development index * delete expectations for developers * devtools * obbject stuff * add * installation * hub sync * idk if i committed already * add usage page for financial statements * add link to reference page * syntax * numbers * nearly --> more than * easier to read code blocks * codespell * removing mention to provider * add 'orientation' for to_dict * info card for output user preference * put it in a code block * correct user_settings.json example * syntax corrections * fix sentence * get rid of floating point mathc * get rid of other floating point math * add companion example notebook for financial statements, and new section * historical prices usage page * codespell * add commitment of traders section to usage * add a note * codespell * get rid of equals sign * Cleanup docs. with @the-praxs * install * obbject extend * spell * HeadTitle thingies * Update obbject_extensions.md * Update obbject_extensions.md * typo * Update architectural_considerations.md * point to the TET pattern * optional vs required * reviewing the patterns. removed the --pre flag under the assumption this will be the final docs for the release cc @deeleeramone * add a walkthrough * spelling * Add more in the introduction * validator examples * update Copper-to-Gold notebook example for V4 * Update README.md * QA Caveats w @the-praxs * info on class outputs * merge add data sources and add data points * disclaimer on cookiecutter * add missing import to example * slight syntax change * missing code block * missing import * update intrinio example syntax * intrinio syntax update * urls * core and provider merged * example syntax * grammar * Update API banner link * quick-fix-docs cc @minhhoang1023 * Update pip install command for v3 * remove --pre note block * update landing image --------- Co-authored-by: Henrique Joaquim <h.joaquim@campus.fct.unl.pt> Co-authored-by: Luqman <luqazino@gmail.com> Co-authored-by: James Maslek <jmaslek11@gmail.com> Co-authored-by: Igor Radovanovic <74266147+IgorWounds@users.noreply.github.com> Co-authored-by: montezdesousa <79287829+montezdesousa@users.noreply.github.com> Co-authored-by: Theodore Aptekarev <aptekarev@gmail.com> Co-authored-by: Pratyush Shukla <ps4534@nyu.edu>
51 lines
2.2 KiB
Markdown
Vendored
51 lines
2.2 KiB
Markdown
Vendored
# OpenBB SDK v3
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[](https://pepy.tech/project/openbb)
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[](https://github.com/OpenBB-finance/OpenBBTerminal)
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| OpenBB is committed to build the future of investment research by focusing on an open source infrastructure accessible to everyone, everywhere. |
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| Check our website at [openbb.co](www.openbb.co) |
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## Overview
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OpenBB SDK provides a convenient way to access raw financial data from multiple data providers. This allows users to build custom financial dashboards and reports in minutes.
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More information on this product can be found [here](https://openbb.co/products/sdk)
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## Installation
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The command below provides access to the core functionalities behind the [OpenBB Terminal](https://openbb.co/products/terminal).
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```python
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pip install openbb==3.2.4
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```
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If you wish to utilize our **Portfolio Optimization** or **Machine Learning / Artificial Intelligence** toolkits, please see instructions [here](https://docs.openbb.co/terminal/installation).
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## Usage
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Access our fully fledged financial SDK with a single line of python code.
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```python
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from openbb_terminal.sdk import openbb
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```
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Everything you need to use the OpenBB SDK can be found on our [Official Documentation](https://docs.openbb.co/sdk).
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Main uses cases can be seen below.
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___
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### RAW FINANCIAL DATA AT YOUR FINGERTIPS
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Access raw financial data from any data source that you are interested. The open source nature of this SDK makes it so that this is an ever-growing project and that everyone can contribute to.
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### GENERATE INSIGHTS 10X FASTER
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For most of the functionalities, adding `_chart` to the function will allow you to visualize the output directly from a Jupyter Notebook. Not only speeding up the time it takes to create a plot for the data you are interested in, but making building custom reports much faster.
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