Eo readme

README.md

@@ -28,69 +28,60 @@
 
 ## Introduction
 
-> Data is everywhere. In order to get the best out of it, one needs to extract it from several sources, make required transformations and load it to a data warehouse for further analysis and explorations. This is where ETL data pipelines come to use.
+Data is everywhere. In order to get the best out of it, one needs to extract it from several sources, make required transformations and load it to a data warehouse for further analysis and explorations. This is where ELT data pipelines come to use.
 
-> Trade involves the transfer of goods and services from one person or entity to another, often in exchange for money. Economists refer to a system or network that allows trade as a market.
+Trade involves the transfer of goods and services from one person or entity to another, often in exchange for money. Economists refer to a system or network that allows trade as a market.
 
-> A cryptocurrency is a digital or virtual currency that is secured by cryptography, which makes it nearly impossible to counterfeit or double-spend. Many cryptocurrencies are decentralized networks based on blockchain technology—a distributed ledger enforced by a disparate network of computers.
+A cryptocurrency is a digital or virtual currency that is secured by cryptography, which makes it nearly impossible to counterfeit or double-spend. Many cryptocurrencies are decentralized networks based on blockchain technology—a distributed ledger enforced by a disparate network of computers.
 
-> A defining feature of cryptocurrencies is that they are generally not issued by any central authority, rendering them theoretically immune to government interference or manipulation.
+A defining feature of cryptocurrencies is that they are generally not issued by any central authority, rendering them theoretically immune to government interference or manipulation.
 
 ## Overview
 
-> A startup called Mela (our client for this week’s project) wants to make it simple for everyone to enter the world of cryptocurrencies and general stock market trade. It also wants to give investors a reliable source of investment while lowering the risk associated with trading cryptocurrencies.
+Our client is A startup called Mela. Mela wants to  make it simple for everyone to enter the world of cryptocurrencies, to give them a reliable source of investment and lower the risk of  trading cryptocurrencies. 
 
-> Although the past performance of any financial market is never a reliable indicator of the future, it is important to run backtests that simulate current and past particular situations as well as their trend over time. Having a clear understanding of the financial system, and stock market trading, and recognizing the complex data engineering systems involved in the crypto and general stock market trading systems are essential.
+Although the past performance of any financial market is never a reliable indicator of the future, it is important to run backtests that simulate current and past particular situations as well as their trend over time. Having a clear understanding of the financial system, and stock market trading, and recognizing the complex data engineering systems involved in the crypto and general stock market trading systems are essential.
 
 ## Objective
 
-> This objective of this project is very straightforward: design and build a robust, reliable, large-scale trading data pipeline, for both crypto and stock market trading that can run various backtests and store various useful artifact in a robust data warehouse system.
+The objective of this project is to design and build a robust, reliable, large-scale trading data pipeline, for both crypto and stock market trading that can run various backtests and store various useful artifact in a robust data warehouse system.
 
-> Users will be prompted with several different stock and crypto trading options and parameters. After processing these parameters users will then be provided with several back testing outputs using different strategies on the specific stock or crypto trading.
+Users will be prompted with several different stock and crypto trading options and parameters. After processing these parameters users will then be provided with several back testing outputs using different strategies on the specific stock or crypto trading.
 
 ## Data
 
-> The data used for generating these back testing results comes from several historical data of stocks and crypto currency trades.
-> These datasets are publicly available and can be found at [yahoo finance](https://help.yahoo.com/kb/SLN2311.html) and [binance](https://www.binance.com/en/landing/data).
-> You can read a brief description of what a K-line or candlestick data is [here](https://www.investopedia.com/terms/c/candlestick.asp).
+The data used for generating these back testing results comes from several historical data of stocks and crypto currency trades.
+These datasets are publicly available and can be found at [yahoo finance](https://help.yahoo.com/kb/SLN2311.html) and [binance](https://www.binance.com/en/landing/data) (see a brief description of what a K-line or candlestick data is [here](https://www.investopedia.com/terms/c/candlestick.asp)).
 
-> Basic features of the data sets:
->
-> - Date: The day the specific trade was recorded
-> - Open: The opening price of the trade at the beginning of the specific day
-> - High: The highest price of the trade for the specific day
-> - Low: The lowest price of the trade for the specific day
-> - Close: The closing price of the trade at the end of the specific day
-> - Adj Close: The closing price after adjustments for all applicable splits and dividend distributions
-> - Volume: The volume of the trade for the specific day
-
-## Requirements
-
-> Pip
-
-> FastApi
 
-> Zookeeper
+Basic features of the data sets:
 
-> kafka-python
+- Date: The day the specific trade was recorded
+- Open: The opening price of the trade at the beginning of the specific day
+- High: The highest price of the trade for the specific day
+- Low: The lowest price of the trade for the specific day
+- Close: The closing price of the trade at the end of the specific day
+- Adj Close: The closing price after adjustments for all applicable splits and dividend distributions
+- Volume: The volume of the trade for the specific day
 
-> Apache kafka
-
-> backtrader and yfinance
-
-> React (nodejs)
-
-> Apache airflow
-
-> Python 3.5 or above
+## Requirements
 
-> Docker and Docker compose
+ * Pip
+ * FastApi
+ * Zookeeper
+ * kafka-python
+ * Apache kafka
+ * backtrader and yfinance
+ * React (nodejs)
+ * Apache airflow
+ * Python 3.5 or above
+ * Docker and Docker compose
 
 You can find the full list of requirements in the requirements.txt file
 
 ## Install
 
-> We highly recommend you create a new virtual environment and install every required modules and libraries on the virtual environment.
+We highly recommend you create a new virtual environment and install every required modules and libraries on the virtual environment.
 
 ### Installing this application
 
@@ -104,7 +95,7 @@ pip install -r requirements.txt
 
 ## Examples
 
-> ### Using this application locally
+### Using this application locally
 
 - One can start using the application by first running the front and back ends.
 - You can run the front-end by running the following command on the terminal
@@ -122,7 +113,7 @@ cd api
 uvicorn app:app --reload
 ```
 
-> ### Interacting with the front end
+### Interacting with the front end
 
 - After running the front end, one can simply go over to the browser and type in [http://localhost:3000](http://localhost:3000). or click this [link](http://localhost:3000)
 - A page similar to this will appear.
@@ -134,39 +125,39 @@ uvicorn app:app --reload
 
 ![](screen_shots/web_app/sign_in.png)
 
-- Enter your emil and password and click on the 'SIGN IN' button.
+- Enter your email and password and click on the 'SIGN IN' button.
 
 - Users will then fill in the parameters that are listed to get the back testing results they want, and click on the 'Run Test' button.
 
 ![](screen_shots/web_app/get_metrics.png)
 
 ## Frontend
 
-> The front end application can be found here in the presentation folder
+The front end application can be found here in the [presentation](presentation) folder
 
 ## Backend
 
-> The back end application can be found here in the api folder
+The back end application can be found here in the [api](api) folder
 
 ## Screenshots
 
-> The detailed use and implementation of the pipelines using Apache Airflow, pipeline summary and interaction, kafka clusters, interaction with the topics on the kafka clusters, front-end images and usage can all be found in this screenshots folder as image files.
+The detailed use and implementation of the pipelines using Apache Airflow, pipeline summary and interaction, kafka clusters, interaction with the topics on the kafka clusters, front-end images and usage can all be found in this [screenshots](screen_shots) folder as image files.
 
 ## Notebooks
 
-> All the notebooks that are used in this project including EDA, data cleaning and summarization along with some machine learning model generations are found here in the Notebooks folder.
+All the notebooks that are used in this project including EDA, data cleaning and summarization along with some machine learning model generations are found here in the [Notebooks](notebooks) folder.
 
 ## Scripts
 
-> All the scripts and modules used for this project relating to interactions with kafka, airflow, and other frameworks along with default parameters and values used will be found here, in the scripts folder.
+All the scripts and modules used for this project relating to interactions with kafka, airflow, and other frameworks along with default parameters and values used will be found here, in the [scripts](scripts) folder.
 
 ## Strategies
 
-> All the back testing strategies and algorithms are found here in the strategies folder.
+All the back testing strategies and algorithms are found here in the [strategies](strategies) folder.
 
 ## Tests
 
-> All the unit and integration tests are found here in the tests folder.
+All the unit and integration tests are found here in the tests folder.
 
 ## Authors