Here is the first tutorial of the course to learn python basics.

Only serious learners are requested to watch. Here my intention is not view count but whoever watch expecting to watch it completely and get some knowledge out of it.

https://t.co/pb0kcJefxK

More from Python

Nano Course On Python For Trading
==========================
Module 1

Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...

... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit
https://t.co/EZt0agsdlV

This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!

In Module 1 of this Nano course, we will learn about :

# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)

# Using Google Colab

Intro link is here on YT: https://t.co/MqMSDBaQri

Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb

You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want

# Importing Libraries

Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
Nano Course On Python For Trading
==========================
Module 4

In this post, I will attempt to teach you how to write a trading strategy in Equity Segment that runs on your PC and create a Telegram bot that sends you buy/sell signals with Stop Loss.


Prerequisite: If you hadn't gone through the earlier modules, I strongly recommend you go through them all. Module 2: https://t.co/pciDOJXyVI

Note:
If you liked my content, you can donate, tip and support me on this link (any amount you prefer)


We are going to implement below strategy:

Rules: There should be three candles -> high of candle 1 > high of candle 2 > high of candle 3 and low of candle 1 < low of candle 2 < low of candle 3, where candle 3 is T-1 day, candle 2 is T-2 day and candle 1 is of T-3 Day, T = today.


If on today(day=T), the stock crosses yesterday high(candle 3), then send a buy signal to your telegram handle with candle 3 low as SL.

Before we get started with code, let's create a telegram bot using BotFather.

Step 1: Search BotFather in the telegram.
Step 2: type /newbot and then give the name to your bot. Refer to the second image as an example

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A brief analysis and comparison of the CSS for Twitter's PWA vs Twitter's legacy desktop website. The difference is dramatic and I'll touch on some reasons why.

Legacy site *downloads* ~630 KB CSS per theme and writing direction.

6,769 rules
9,252 selectors
16.7k declarations
3,370 unique declarations
44 media queries
36 unique colors
50 unique background colors
46 unique font sizes
39 unique z-indices

https://t.co/qyl4Bt1i5x


PWA *incrementally generates* ~30 KB CSS that handles all themes and writing directions.

735 rules
740 selectors
757 declarations
730 unique declarations
0 media queries
11 unique colors
32 unique background colors
15 unique font sizes
7 unique z-indices

https://t.co/w7oNG5KUkJ


The legacy site's CSS is what happens when hundreds of people directly write CSS over many years. Specificity wars, redundancy, a house of cards that can't be fixed. The result is extremely inefficient and error-prone styling that punishes users and developers.

The PWA's CSS is generated on-demand by a JS framework that manages styles and outputs "atomic CSS". The framework can enforce strict constraints and perform optimisations, which is why the CSS is so much smaller and safer. Style conflicts and unbounded CSS growth are avoided.