Showing posts with label Windows 10. Show all posts

Sunday, March 25, 2018

Remote Accessing Raspberry Pi 3 From Win 10| 2018-03-25

Just captured the screenshots for the process setting up remote access to Pi3 from Win 10
Click the link below for detail instructions.

Remote Accessing Raspberry Pi3 From Win 10

Friday, November 10, 2017

Create Python Backtest With Jupyter Notebook Anaconda 3.5.0.1 On Windows 10| 2017-11-11

Backtest With Jupyter Notebook Anaconda 3.5.0.1

Just walkthrough the whole process of creating Python backtest in Anaconda, Windows 10.

The process is broken down into 5 major steps:
00x | Install Anaconda
10x | Get online stock (e.g. AAPL) | Market Data
20x | Create trade strategy | Strategy Class
30x | Generate trade signal | Signal Class
40x | Create investment portfolio | Portfolio Class
50x | Perfomance review | PnL + Graphing

A timeline is provided below for easy navigation:
In case you just want to use the Anaconda root setup, skip step 'Ana002'

mm:ss
00:00 - 03:02 ||Ana001| Install Anaconda
03:04 - 10:02 ||Ana002|Setup different environment other than root - optional step*
10:04 - 19:02 ||Ana101| Get Apple stock data from Yahoo Finance, save to local drive as Excel
19:04 - 29:11 ||Ana201| Create Strategy - calculate moving averages
29:12 - 35:53 ||Ana202| Create Strategy - get stock trend
35:55 - 41:22 ||Ana301| Get Trade Signal and Generate Order
41:24 - 49:50 ||Ana401402| Create Investment Portfolio and Trade Details
49:52 - 59:03 ||Ana501502| Calculate Profit and Loss and Graphing

* install optional Python packages that your project requires
** the strategy mentioned assumes zero borrowing cost so that whenever short position occurs,
we can borrow unlimited amount of money without needing to pay a penny of interest.
This is not real in real world. So just be aware of that.

Here's the 59-min video(Complete Walkthrough - Jupyter Notebook Anaconda):

*** this video is rendered in 1.05x speed; feel free to visit the original speed videos below.

Install Anaconda 3.5.0.1(Ana001)

Setup Environment In Anaconda 3.5.0.1(Ana002) - Optional

Get Online Stock Data + Save To Local Drive(Ana101)

Form Trade Strategy - Calculate Moving Average (Ana201)

Form Trade Strategy - Get Stock Trend (Ana202)

Generate Trade Signal - Get Stock Trend (Ana301)

Create Investment Portfolio (Ana401402)

Measuring Performance & Graphing (Ana501502)

Backtest With Python Default Editor

My Thought

Comparing to buidling Python strategy backtest in default Python editor,
the Anaconda Jupyter Notebook takes a bit of time to get used to.
It takes time to load up the Jupyter Notebook while such load time is minimal in Python default editor.

But from layman's perspective, setting up multiple environments and installing packages
through the Anaconda Navigator are intuitive.
Anaconda basically organizes the folders under the 'env' folder.
That's good folder management.

In the future, I'll try using Sublime Text 3 to route to the Anaconda's environment folder.
See if I can take advantage of Sublime Text' speed while maintaining proper environment folder
management.

If you find this article helpful, feel free to discuss on my Facebook:

www.facebook.com/clueple

Disclaimer:
Everything shown in this video is just the author's personal experience with Anaconda.
All mentioned assumptions and tactics are used as demonstration for education purpose.
Trade details, not limited to, leverage level, deposit amount, transactions fees, and
any costs associated with the strategy are not meant to be complete.

No investment decision should be based on any information provided in this video.
No professional advice are provided or implied whatsoever.

Viewers are solely responsible for any loss associated to consumption of this video.

Monday, November 6, 2017

Setup Jupyter Notebook & Anaconda Environment On Windows 10

Jupyter Notebook

Just record how to create Anaconda environment to use Jupyter Notebook in folders other than the root folder, Windows 10.

#create_anaconda_environment_on_win10, #jupyter_notebook_on_anaconda, #use_jupyter_notebook_in_folders_other_than_root_folder,

Thursday, August 24, 2017

Setup Python 3.6.2 Virtual Environment For Trade + Machine Learning Setup| Windows 10 Sublime Text 3

Part 1

Part1

In this video
I'll be showing how to setup Python on Windows 10

Look up for the Python installation from your browser
and install the one that fits your system

Here I'm downloading the 64-bit Windows version

Save it to your download folder
and double click to install

Untick things that are not needed
and custom install to the drive you want

Untick the optional features
and set the destination folder

In this case
I'll be installing Python to F drive folder "py362"

Hit "OK" and start installation

You can now remove the Python installer

Now we're going to install virtualenv

Open command prompt

Navigate to the system Python location
which is F:\py362\Scripts

from there
we pip install virtualenv

Hit [Enter]
and wait for the process

you can type pip list to check whether virtualenv is installed to the system

Part 2

We're now creating a folder in F drive to hold our virtual environment

Go to command prompt
Go to F drive and type md space "Trade"
We'll be using this folder to hold our Python trade projects

Part 3

Open a new command prompt

and navigate to our system Python location
which is F:\py362\Scripts

hit [Enter] and install a new virtual environment
to the path
F:\Trade\TradeEnv
then hit [Enter] to start installation

Exit command prompt
and go to the path to see whether the virtual environment is installed

Jump back to browser
and download Sublime Text 3
Click to download the one that fits your system

Once it's downloaded
extract all files
then cut and paste the Sublime Text folder
to your destination folder

Open up the Sublime Text folder
and doubleclick the execute file to start programming

Let's start typing some Python code
Save it as a Python file

Before you run the code
you go to Tools -> Build System and tick Python

But when you hit [Ctrl] [B] to run the code
you get error message

That's why we need to create new build
to point to our virtual environment

From the untitled sublime build file
we need to paste some codes

We can look up for these codes from web

Before we save
we need to change the "python" path
to our virtual environment

I just name it with my environment's name
so that I can easily remember

Go back to your Python file
and tick the Sublime build we've just created
and run the Python code to check if it works

Yeah! It works

Part 4

If you want to move the output panel
from bottom to right

simply hit [Ctrl], [Shift], [P]
and type "install package"

Hit [Ctrl], [Shift], [P] again
and type "install"
Hit it and you'll be able to type "buildview"

click the only selection
and wait for the installation

Now you can hit [Alt] [Shift] [2]
and see a split in between

Simply run the code again
and drag the result panel
to the right

Then you can now see the right side
displays the code result

Now
we're going to pip install several packages for trade

Open command prompt

Navigate to the virtual environment's Scripts folder
pip install pandas
This is a popular package to read and process data

We then pip install xlrd
to let us read and write Excel file with Python

Pip install matplotlib
We use this one to plot graph

We also need beautifulsoup 4 to grab web data

exit command prompt

I'm going to create a new Python file to test these packages
Before saving, make sure you're coding in the virtual environment

Save the file

We're going to read this csv file with Python packages

Let me type and run the code

Ooops I type the wrong file format excel instead of csv

Go back to change to csv in our code
and press [Ctrl] [B] to run it

There we go!

Thanks for watching

Please note that you can also install numpy + mkl, scipy, and sklearn for machine learning

Feel free to discuss trade algo at
www.facebook.com/clueple

Clueple