Mobile app development is a massive skill in the 21st century. In fact, the revenue of the mobile app market worldwide is mobile app revenue in 2022 is $437 billion USD. (Statista)

A mobile app developer is a programmer who focuses on software creation for mobile devices such as smartphones or wearables.

Most mobile app developers create smartphone apps for the Android, macOS, or Windows mobile operating system.

This article will show you the five areas of focus you could pursue to become a mobile app developer.

#1 – Android App Developer

An Android app developer is a programmer who focuses on software creation for mobile devices such as smartphones or wearables using the Android operating system.

How much does an Android App Developer make per year?

The average annual income of an Android App Developer in the United States is between $85,000 and $126,577 with an average of $106,923 and a statistical median of $107,343 per year.

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

#2 – iOS App Developer

An iOS app developer is a programmer who focuses on software creation for Apple mobile devices such as iPhones or wearables such as Apple Watches. Most mobile app developers create smartphone apps for the iOS or watchOS mobile operating systems using the Swift programming language.

How much does an iOS App Developer make per year?

The average annual income of an iOS Developer in the United States is between $83,351 and $145,000 with an average of $110,331 and a statistical median of $111,716 per year.

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

#3 – Firebase Developer

Firebase is a Google-based platform to create mobile and web applications easily. Firebase developers are programmers who create mobile apps with Firebase

The average annual income of a Firebase Developer is approximately $80,000 according to PayScale (source).

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

#4 – Flutter Developer

A Flutter Developer developer creates, edits, analyzes, debugs, and supervises the development of Android mobile apps written in the Flutter programming framework using the Dart programming language.

The average income of a Flutter developer in the US is $112,125 per year or $57.50 per hour. Entry-level Flutter developers start with approximately $100,000 per year. Experienced developers make up to $159,900 per year. (source)

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

#5 – Kotlin Developer

A Kotlin Developer is an Android app programmer using the Kotlin programming language.

Kotlin is JVM compatible and, thus, fully compatible with Java. That’s why it’s often used as an alternative to Java when developing Android applications.

The average annual income of a Kotlin Developer is $102,000 according to PayScale and averages between $113,000 to $147,000 per year according to Ziprecruiter.

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

#6 – Swift Developer

A Swift developer is a programmer who creates software and mobile applications for the Swift programming language for iOS, iPadOS, macOS, tvOS, and watchOS. (Source)

The average annual income of a Swift Developer is between $93,000 (25th percentile) and $114,500 (75th percentile) according to Ziprecruiter (source).

Learn More: I’ve written a full guide on this career path and published it on the Finxter blog here.

Bonus #7 – Alexa Developer

Alexa is the cloud-based voice service distributed and sold by Amazon. It is available on hundreds of millions of devices and from third-party device manufacturers.

An Alexa developer creates voice applications, so-called Alexa Skills, that run on the Alexa mobile device using the Alexa developer environment.

The average income of an Alexa skill developer in the US is $88,617 per year according to ZipRecruiter. This is approximately $42 per hour, $1,704 per week, or $7,385 per month.

Conclusion

A mobile app developer is a programmer who focuses on software creation for mobile devices such as smartphones or wearables. Most mobile app developers create smartphone apps for the Android, macOS, or Windows mobile operating system.

This article has shown you six main areas of focus. The technologies presented here overlap significantly but I hope reading this article has given you an initial glimpse into the world of mobile app development.

The pcb appears to work fairly well for adapting a 2242 m2 to the steam deck, it doesn't collide with anything on the motherboard or put any extra strain on any cables. However, it does make the heat spreader bow a tiny bit. The back plate reassembled without issue. pic.twitter.com/4j4LVbS0NG

— Belly Jelly (@TheSmcelrea) June 21, 2022

Basic Challenge

Here’s the content of an example CSV file "my_file.csv" used in our code snippet below:

Name,Job,Age,Income

Alice,Programmer,23,110000

Bob,Executive,34,90000

Carl,Sales,45,50000

If you visualize this CSV in table form, it looks like this:

Name	Job	Age	Income
Alice	Programmer	23	110000
Bob	Executive	34	90000
Carl	Sales	45	50000

The basic problem is to convert the CSV file "my_file.csv" to a new TXT file "my_file.txt" as is without changing its content

Name,Job,Age,Income

Alice,Programmer,23,110000

Bob,Executive,34,90000

Carl,Sales,45,50000

We start with exploring this basic challenge and build from there by changing the delimiter and using Pandas to access individual columns.

But first things first: How to convert a CSV file to a TXT file without changing its contents?

Method 1: CSV to TXT Unchanged

If you want to keep the content (including the delimiter ',') in the CSV file unmodified, the conversion is simple: read the .csv file and write its content into a new .txt file using the open(), read(), and write() functions without importing any library.

In other words, perform the three steps to write a CSV to a TXT file unmodified:

1. Open the CSV file in reading mode and the TXT file in writing mode.
2. Read the CSV file and store it in a variable.
3. Write the content into the TXT file.

Here’s the code snippet that solves our basic challenge:

# 1. Open the CSV file in reading mode and the TXT file in writing mode

with open('my_file.csv', 'r') as f_in, open('my_file.txt', 'w') as f_out: # 2. Read the CSV file and store in variable content = f_in.read() # 3. Write the content into the TXT file f_out.write(content)

Little-Known Fact: Python allows multiple expressions in the context manager (with opening line) if you separate them with a comma.

The content of the .csv and .txt files is identical:

Name,Job,Age,Income

Alice,Programmer,23,110000

Bob,Executive,34,90000

Carl,Sales,45,50000

So far, so good. But what if you have a slightly different problem:

Method 2: CSV to TXT Empty Space Delimiter

Challenge: How to convert a CSV file to a TXT file in Python by replacing the delimiter ',' with the empty space ' '?

Example: Convert the following file 'my_file.csv'…

Name,Job,Age,Income

Alice,Programmer,23,110000

Bob,Executive,34,90000

Carl,Sales,45,50000

… to this file 'my_file.txt' …

Name Job Age Income

Alice Programmer 23 110000

Bob Executive 34 90000

Carl Sales 45 50000

Here’s the simple solution to this challenge:

If you want to change the delimiter ',' to an empty string ' ' in the new TXT file, read the .csv file and write its content into a new .txt file using the open(), read(), string.replace(), and write() functions without importing any library.

To convert a CSV to a TXT file in Python, perform the following steps:

1. Open the CSV file in reading mode and the TXT file in writing mode.
2. Read the CSV file into a string.
3. Create a new string by replacing all occurrences of the delimiter ',' with the empty string ' '.
4. Write the content into the TXT file.

with open('my_file.csv', 'r') as f_in, open('my_file.txt', 'w') as f_out: content = f_in.read().replace(',', ' ') f_out.write(content)

So far, so good. But in Python, there are always many ways to solve a problem. Let’s have a look at a powerful alternative to the no-library approach used before:

Method 3: CSV to TXT using Pandas

Assuming you’ve already installed pandas in your local environment, you can write a CSV to a TXT file in Python pandas using the following four steps:

1. Import the pandas library.
2. Read the CSV file into a DataFrame using pd.read_csv().
3. Convert the DataFrame to a String using the built-in str() function.
4. Print the string to a file using the file argument of the print() function, for example.

Here’s the basic Python example:

import pandas as pd df = pd.read_csv('my_file.csv')

content = str(df)

print(content, file=open('my_file.txt', 'w'))

Little-Known Fact: Python’s print() function allows you to write a string directly into a file object if you use the file argument as shown in the code snippet.

The output of the previous code snippet is as follows:

 Name Job Age Income

0 Alice Programmer 23 110000

1 Bob Executive 34 90000

2 Carl Sales 45 50000

Beautiful, isn’t it?

Let’s have a look at the last variation of the “CSV to TXT” problem addressed in this tutorial:

Method 4: CSV Columns or Rows to TXT using Pandas

How to write one or more individual columns or rows of the CSV file into a TXT file using Python Pandas?

1. Import the pandas library.
2. Read the CSV file into a DataFrame using pd.read_csv().
3. Select the column(s) or row(s) to write into the TXT file from the DataFrame using Pandas indexing or slicing.
4. Call df.to_string() to convert the DataFrame to a string in a human-readable way.
5. Print the string to a file using the file argument of the print() function, for example.

import pandas as pd df = pd.read_csv('my_file.csv')

content = str(df['Name'])

print(content, file=open('my_file.txt', 'w'))

The content in a new file 'my_file.txt':

0 Alice

1 Bob

2 Carl

Of course, you can also select individual rows or multiple columns like so:

import pandas as pd df = pd.read_csv('my_file.csv')

content = df['Name'][:2].to_string()

print(content, file=open('my_file.txt', 'w'))

The content of the new file 'my_file.txt' shows that only the first two rows have been taken due to the slicing operation [:2] in the previous code snippet:

0 Alice

1 Bob

Done! You’ve earned some programming enjoyment:

Programmer Humor

Question: How did the programmer die in the shower? ☠

❗ Answer: They read the shampoo bottle instructions:
Lather. Rinse. Repeat.

Conclusion

I hope you enjoyed reading this article and learned something new. Feel free to join our email newsletter with free cheat sheets and weekly Python tutorials:

What are Polygon and MATIC all about and why is another blockchain needed? You will find answers to these questions in this article.

The article starts with problems plaguing Ethereum, workable solutions to the problem, and then dives into more details of the Polygon network, its history, tokenomics, and an overview of the Polygon SDK.

Ethereum Scaling Problems

To date, Ethereum remains the most widely adopted and actively used blockchain in the current scenario.

It gained popularity because of its offering of smart contract functionality, variety of tools, ecosystem, and sizable community support.

However, using Ethereum comes at a price because of its high gas fees, network clogging because of many users, and lower transactions per second (approximately ~30 tps).

Ethereum TPS

Why do transactions on Ethereum (or also Bitcoin) take so long?

The answer is in the blockchain‘s structure. In these blockchains, before we approve a transaction, it must pass through various stages – queue in the transaction pools, mining, distribution, and validation.

Ethereum, also called layer-1 or base layer, must handle all the activities before the transaction gets included in the block and the block makes it to the chain.

Inevitably, there are delays in processing which affect the user experience and scalability at Ethereum or layer-1. Compare this with centralized systems such as Paypal or Visa with a TPS value as high as ~24,000.

Solutions to Scaling

You may wonder, “why Ethereum or layer-1 itself can’t be scaled ?”.

First, the problem is that sophistication levels introduced at layer-1 to solve scaling problems mean writing more code at this layer, resulting in more time to bring improvements, new features to Ethereum, and countless discussions.

Second, more code at layer-1 means compromising security for scalability.

Scaling problems such as the one described above have multiple solutions.

As this tutorial focuses mostly on Polygon, the other scaling solutions are mentioned here only for reference. We can divide the scaling solutions mainly as On-Chain and Off-Chain and further classified as in the below fig.

Most of the time, the names layer-2 or side chains are applied interchangeably, but there is a difference. While layer-2 inherits the security of the Ethereum network (mainnet), sidechains rely on their own security model.

In the next section, we start with Polygon, a sidechain solution (blockchain that runs parallel to the mainnet Ethereum), and how it solves the Ethereum scaling problem.

Polygon Origins

Originally known as Matic networks, it was started in 2017, in India by Anurag Arjun, Sandeep Nailwal, Jaynti Kanani, and Mihailo Bjelic.

Initially, it offered two solutions to the Ethereum scaling problem.

• PoS sidechain, a proof of stake Ethereum sidechain
• Plasma chain

In 2021, it was renamed or rebranded as Polygon.

Polygon’s goal has evolved from offering Ethereum network layer-2 to developing the entire blockchain network architecture for developers, as seen by the name change.

Polygon is presently working on a roadmap for connecting numerous layer-2 solutions forming a multi-layer-2 blockchain network that can coexist with the Ethereum network.

The existing Polygon solutions PoS sidechain and the Plasma chain will continue to exist and will be an important part of the growing Polygon multichain system.

Tokenomics and dApps

MATIC is the token name offered by the Polygon Network. Polygon MATIC began as a testnet in October 2017 and then transitioned to mainnet later that year.

During its maiden offering in April 2019, the company raised $5.6 million in ETH by selling 1.9 billion MATIC tokens over the course of 20 days. They formed the Matic Network in 2020, and Matic changed its name to Polygon Network in February 2021.

AAVE debuted on the platform in April 2021, enhancing the Polygon network’s value. Other famous dApps (Defi, NFTs, and Dex) launched on Polygon include Quickswap, KogeFarm, Aavegotchi, etc.

Polygon SDK Overview

Polygon is more of a protocol than a single solution to scaling, and up to this point, the Polygon framework aims to support two types of Ethereum compatible solutions: Secured chains and Stand-alone chains.

Secured Chains

Secured chains are chains that have the potential to internalize, make use of the existing security of the Ethereum network.

It allows developers to use Polygon’s scalability while still employing the Ethereum network’s security. As secured chains don’t have their own security model, they offer better security and lesser flexibility.

Secured chains are suitable for security focussed projects and startups. An example of a secured chain is Rollups.

Stand-Alone Chains

Stand-alone chains fully define their own security model of consensus mechanisms such as Proof Of Stake (PoS) and Delegated Proof Of Stake(dPoS).

They have their own miner or validator pools.

They offer better flexibility and independence but lesser security because of their own security mechanism in place.

Stand-alone chains are suitable for enterprise blockchains and projects needing more flexibility than security. An example of Stand-alone chains is sidechains.

The Polygon SDK offering can be summarized with the picture below:

Dominance Over Other Layer-2 Blockchain Solutions

Polygon offers several advantages over other blockchain ecosystems for layer-2 scaling like Polkadot (DOT), Avalanche (AVAX), and Cosmos (ATOM).

• Polygon provides developers a fully customizable tech stack, with a user experience akin to Ethereum.
• Polygon can use the full capacity of the Ethereum network thanks to the multi-chain technology, which allows it to do so without losing throughput or security.
• Polygon provides blockchain speed-up solutions, allowing for faster transactions and reduced gas rates than the Ethereum mainnet. Polygon also plans to provide developers with tools for creating Ethereum-compatible blockchain networks.

Polygon is thus critical for developers and small-to-medium-sized enterprises concerned with Ethereum’s network congestion. As a long-term scaling solution, Polygon can provide a wide range of utilities for developers. Some people believe that this potential gives the MATIC token a one-of-a-kind value proposition.

Polygon For a User

Users who interact with Polygon frequently only view the blockchain as a whole, and the underlying architecture is unimportant to them.

Polygon allows any Ethereum-compatible web wallet, such as Metamask, to connect, acquire funds (MATIC), and interact with dApps deployed across the network.

For a long time, OpenSea has permitted the minting and trading of NFTs on Polygon.

Conclusion

This article discussed the Ethereum scalability issue and how the Polygon sidechain network can help solve the base-layer or layer-1 issues, as well as an overview of the Polygon SDK framework and how it compares to alternative solutions at this time.

The next posts will explore more on the Polygon networks and hands-on developing dApps on Polygon.

Nerd Humor