anandology

The resource for this talk will be updated here soon.

anandology

API - V1

Basic Types

Create a circle:

circle()
circle(r=50)
circle(cx=100, cy=100, r=50)

anandology

def test_sendmail(monkeypatch):
	emails = []

	def mock_sendmail(self, from_addr, to_addrs, msg, mail_options=(), rcpt_options=()):
		emails.append(dict(from_addr=from_addr, to_addrs=to_addrs, msg=msg))

	monkeypatch.setattr(smtplib.SMTP, "sendmail", mock_sendmail)

	frappe.sendmail(

anandology

This gist demonstrates one of the issues with the new build system of Frappe.

How to reproduce

Step 1

Add the sq.js and square.bundle.js from gist to apps/frappe/frappe/public/js in your bench.

Step 2

anandology

Trying to install Lineage OS on MI A2 (jasmine_sprout) follow the instructions from:

https://wiki.lineageos.org/devices/jasmine_sprout/install

Unlocking the bootloader

1. Enable OEM unlock - done
2. fastboot oem unlock - done

Temporarily booting a custom recovery using fastboot

anandology

function grid() {
  push();
  noFill();
  stroke(200);
  for (var x=0; x<width; x+=50) {
    line(x, 0, x, height);
  }
  for (var y=0; y<height; y+=50) {
    line(0, y, width, y);

anandology

Write a CLI application to list the number of covid19 cases and deaths in India.

You can use the following API for getting that data:

https://github.com/anandology/covid19

The required interface is:

$ python covid19.py cases 

STATE CONFIRMED ACTIVE DEATHS

anandology

{
  "india": {
    "confirmed": 586,
    "active": 534,
    "deaths": 10,
    "recovered": 42,
    "indians": 543,
    "foreigners": 43
  },
  "states": {

anandology

/*
FILE: ~/.jupyter/custom/custom.css

Custom CSS to optimize the notebook presentation in full-screen when zoomed in.
*/
@media all and (max-width: 800px) {
    .prompt {
        display: none !important;
    }
    #header-container, #maintoolbar, #menubar {

anandology

# import pandas as pd
from .heavy_modules import pandas as pd

# from google.cloud import bigquery
from .heavy_modules import google_cloud_bigquery as bigquery

def foo(path):
    df = pd.read_csv(path)
    ...