raymondctc

<LinearLayout 
  android:width="wrap_content"
  android:height="wrap_content"
  android:descendantFocusability="beforeDescendants"
  android:orientation="vertical">
  <PostView ... />
  <PublisherAdView ... />
</LinearLayout>

raymondctc

High number of downloads

• Excellent app discovery
  • Play Store keyword, screenshot, screen recordings optimization (ASO)
  • New app store possiblities (e.g. Samsung Galaxy Store)
  • App support different locales
  • Support various device types
  • App SEO
  • Instant app trial
• Excellent app stability, quality
• Ref: "Build for billions"

raymondctc

https://click.liftoff.io/v1/campaign_click/ZtQ56GJO6u0pi_WkT0KZOP0cxwJM4LH1Hq3A4IHakkAGwA8VOfsym12_OQySzuGM_EvOUDJnbiLo4957j_fB2dN3_Z0OqXTwHKzDK-qQy14vUmbOL00mwxdD6jHqBSqAvun10jlwUGbN3NU-qei6bKwKeG-vS0x7oW55NOLkIOwrQ8Kbdzm2gF8_n-3_6bMPpxAKjl8L_pnSo9QJAoKDhjGbNwJiVXD-QzZRQSCCDblf6mr478DWzRalrX3hte1RYprIidDy1NhwCxADxx4J1KliUM-NR1xAS3WrEtQwrj8XGdnxX8gX49YmEAtkWkgTcpppSLu_Ey-9jsYtGL6g
https://click.liftoff.io/v1/campaign_click/slACVIKo_BPYKYD02-2uxxX2tL3zmKx3VolaiHZHXuUmE3uRtrt44SvLlvgJAIfC0OQRnjhChTMI27JPcVfaXx9jKPQeu8i_ImWZs7mxzxZaYnuhWJs6HR44A4_E_53eQKCgfPXWjBN_hgMtUyBhIHPIH94G6hmtXYbGs4jy8mj6VVc13FNaqu0klWzyzSDAkle_seoo-R9f8E1867qSr_QgO3lli1Mend3-XhIIh2vfvJD5nuzchtEMF5p6ZK_HurnP8c1-CajVgVxXTFM0o44fUIS0DRhxm2CpTgsDQtxF52iPCzOalim3iuUzTjig53aqeIFXR5yi-yM4zBLCyOLgNuAuwHM_RQ?click_x=179&click_y=16&click_time=1591778201544&open_method=mraid
https://click.liftoff.io/v1/campaign_click/MScpAjNuzPKsm3qM5-jhjEfuX_F0r-XLXEV78oRW5VlF1dHb5USSL-CCsI42caEO5pZNshf1LsRq0pIhnKeRcnN3hSjNesOvNJ5kfX8TfAU-uloL2gRDVIeqhLDGmNkH-Zr1h

raymondctc

import sys

f = open("device_data.txt", "r")
lines = f.readlines()

count = 0
tempString = ""
for line in lines:
    if count % 2 == 0:
        tempString = line.replace("\n", "")

raymondctc

import fetch from "node-fetch";

const tasks = {
  "tasks": {}
}

const TOKEN = ""

const excludedIndex = [0, 1, 4, 5, 6, 7, 8, 9, 10, 23, 24]

raymondctc

import os
from PIL import Image, ImageEnhance

def apply_monotone(image_path, output_path, color=(0, 0, 255)):
    """Apply a monotone filter while preserving transparency."""
    img = Image.open(image_path).convert("RGBA")  # Ensure RGBA mode
    r, g, b, alpha = img.split()  # Separate channels

    # Convert image to grayscale
    grayscale = ImageEnhance.Color(img).enhance(0)