Swapcard

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As the popularity of Ethereum grows, the need for an efficient and scalable network becomes increasingly crucial. The current limitations of Ethereum’s Layer 1, including slow transaction times and high gas fees, hinder its ability to handle the growing demand. This is where Layer 2 scalability solution comes in. By moving some of the computation off-chain, Layer 2 solutions such as State channels, Plasma, and Rollups aim to improve transaction throughput and reduce fees, providing a more efficient and scalable network for developers and users alike. With the increasing adoption of decentralized applications and the potential for mass adoption, understanding and utilizing Layer 2 solutions is becoming increasingly important for developers and users to ensure the continued growth and success of the Ethereum ecosystem. Understanding State Channels and How They Work State channels, powered by Filecoin and Consensys, were the first scalability solution I ever came across, addressing issues related to the problems with Ethereum (scalability). I took a curiosity dive at the time to learn more, and I found this amazing blog by the , an indexing protocol for querying networks like Ethereum and IPFS. Graph Their platform enables developers to create open APIs called subgraphs, which provide easy access to data. https://thegraph.com/blog/the-graph-brings-state-channels-to-ethereum/?embedable=true State Channels provide a very broad and straightforward approach to how blockchain interacts and are mostly conducted off-chain. This reduces the risk to participants without compromising security. One of the most essential features is that it also helps to address the concerns of high gas fees and slow transaction processing times, both of which are well-known characteristics of the Ethereum network. This was done by enabling two or more parties to conduct multiple off-chain transactions without having to broadcast every transaction to the Ethereum network. Instead, only the channel’s start and final states are broadcasted to the network, decreasing the amount of computation required while improving scalability. Finally, unlike chains, channels operate on a fixed set of live participants. Channel networks help to ease some of this, however, due to routing and liquidity concerns, they are currently unviable as solutions (along with a compounding of the copy problem mentioned above). The always-on characteristic of channels is likewise unresolved. Use Cases State channels have a wide range of real-world use cases, from micropayments and gaming to decentralized finance (DeFi) and peer-to-peer marketplaces. One example of a state channel in action is the , a decentralized off-chain payment network that uses state channels to enable fast and cheap payments on the Ethereum network. Raiden Network Additionally, state channels can reduce fees for users by minimizing the number of transactions that need to be executed on the main chain. This is because only the initial opening and final closing of the channel require a transaction on the main chain, while all subsequent transactions can take place off-chain. Furthermore, state channels can offer increased privacy for users, as transactions that occur off-chain are not visible to the wider network. This can be particularly important for certain use cases, such as in financial transactions or other sensitive applications. Below, is a Monorepo by State Channel of various applications using the state channel: https://github.com/statechannels/apps?embedable=true Exploring the Benefits and Mechanics of Plasma Founded by the founder of Ethereum, Vitalik Buterin, alongside Joseph Poon, the duo published back in 2017 where they introduced a new layer-2 scalability solution called Plasma. a paper Plasma is a scalability framework for public blockchains such as Ethereum. Plasma chains, as defined in the original Plasma whitepaper, are created on top of another blockchain (called a “root chain”). Each “child chain” extends from the root chain and is generally maintained by a smart contract published on the parent chain. This implies that Plasma may achieve far faster transaction throughput than the main Ethereum chain alone while maintaining the security and decentralization that make Ethereum so efficient. The Plasma contract functions, among other things, as a allowing users to move assets between Ethereum Mainnet and the plasma chain. Although this makes them similar to , plasma chains benefit — at least, to some extent — from Ethereum Mainnet’s security. bridge sidechains This is unlike sidechains that are solely responsible for their security. It is also important to note that one of the key benefits of Plasma is increased scalability, and it achieves this by moving some of the computational work off-chain. This implies that more transactions can be completed at a faster rate while maintaining network security and integrity. Another significant benefit of Plasma is the significant reduction in transaction fees made possible by its unique feature of processing on-chain transactions off-chain, making it an appealing option for organizations and individuals looking to build on the Ethereum network in a more cost-effective and efficient manner. Due to Plansma’s unique approach to handling large volumes of data and transactions without overburdening the main Ethereum network or sacrificing performance and security, dApps that intend to scale to millions of users and are built on the Ethereum network often find it to be a good layer 2 to build on. Overall, Plasma represents a significant advancement in the Ethereum ecosystem, offering a range of benefits that make it an attractive solution for businesses, developers, and users alike. Building on Plasma: is a Solidity library that defines a generic transaction format for Ethereum-based applications. It uses a list of five items, including txType, inputs, outputs, txData, and metaData. GenericTransaction The library provides functions for decoding a transaction from RLP-encoded bytes, getting an output at a specific index, and decoding an RLP item to an output. It also includes a struct for a transaction and an output to store the decoded data. The library is designed for other Solidity contracts to process generic transactions in a standardized manner. So, let’s say you deposit some funds into the Plasma contract. You can then use the function to initiate an exit process for those funds, meaning you want to withdraw them from the Plasma contract. startExit This process can take a little bit of time to complete, but once it’s finished, you can use the function to complete the withdrawal process and receive your funds. finalizeExit Of course, the actual implementation of a Plasma contract would be far more complicated, including elements like fraud proofs and block confirmation. But hopefully, this example gives you an idea of how Plasma can be used in practice. https://gist.github.com/LucidSamuel/c46778a8f169d2d7b795258c39164fcf?embedable=true Getting Started With Rollups Rollups are a type of scaling solution designed to address the issues of high transaction fees and slow processing times experienced on the Ethereum network. Similar to other Layer 2 solutions like Plasma and state channels, Rollups move computational work off-chain. However, instead of using a separate chain or sidechain, Rollups utilize a smart contract on the Ethereum mainnet to verify and batch transactions. This approach enables Rollups to achieve high levels of scalability while still maintaining the security and decentralization of the Ethereum network. Rollups are a promising solution for improving Ethereum’s scalability and reducing gas costs. They provide several benefits, such as increasing the number of transactions processed per second on the network and reducing transaction processing times and congestion. By batching multiple transactions together, Rollups significantly lower the amount of gas required to execute transactions on the network, resulting in lower gas fees. Despite these benefits, Rollups maintain the security and decentralization of the Ethereum network since they rely on a smart contract on the Ethereum mainnet for verification. This ensures that Rollups remain secure and resistant to attacks, providing users with peace of mind when using the network. If you’re a developer looking to get started with Rollups, here’s an example of a complete Ethereum DeFi swap and bridge application that makes use of Rollups for scaling: First, let’s start with the smart contract for the Rollup: pragma solidity ^0.8.0;

contract MyRollup {
    struct Transaction {
        address from;
        address to;
        uint amount;
    }

    Transaction[] public transactions;

    function batchTransfer(Transaction[] memory _txs) public {
        for (uint i = 0; i < _txs.length; i++) {
            transactions.push(_txs[i]);
        }
    }

    function processBatch() public {
        for (uint i = 0; i < transactions.length; i++) {
            Transaction memory tx = transactions[i];
            tx.to.transfer(tx.amount);
        }
        delete transactions;
    }
} This Rollup contract allows for batch transactions to be submitted and processed off-chain, reducing the gas fees and congestion on the Ethereum mainnet. Next, we have the DeFi swap smart contract: pragma solidity ^0.8.0;

interface IERC20 {
    function transferFrom(address sender, address recipient, uint256 amount) external returns (bool);
    function approve(address spender, uint256 amount) external returns (bool);
    function balanceOf(address account) external view returns (uint256);
}

contract MyDeFiSwap {
    IERC20 public token;

    constructor(address _token) {
        token = IERC20(_token);
    }

    function swap(uint amount) public {
        // Transfer tokens from user to contract
        require(token.transferFrom(msg.sender, address(this), amount), "Transfer failed");

        // Perform swap logic here
        // ...

        // Transfer swapped tokens back to user
        require(token.transfer(msg.sender, swappedAmount), "Transfer failed");
    }
} The function in this contract allows users to swap tokens by transferring them to the contract, performing the swap, and transferring the swapped tokens back to the user. swap Finally, we have the bridge contract that interacts with the Rollup and DeFi swap contracts: pragma solidity ^0.8.0;

interface IMyRollup {
    function batchTransfer(Transaction[] memory _txs) external;
    function processBatch() external;
}

interface IMyDeFiSwap {
    function swap(uint amount) external;
}

contract MyBridge {
    IMyRollup public rollup;
    IMyDeFiSwap public swap;

    constructor(address _rollup, address _swap) {
        rollup = IMyRollup(_rollup);
        swap = IMyDeFiSwap(_swap);
    }

    function swapAndBatchTransfer(Transaction[] memory _txs, uint swapAmount) public {
        swap.swap(swapAmount);
        rollup.batchTransfer(_txs);
        rollup.processBatch();
    }
} The function in this contract performs a token swap on the DeFi swap contract, batches the transfer of tokens to multiple recipients using the Rollup contract, and then processes the batch off-chain to reduce gas fees. swapAndBatchTransfer It is important to note that in a real-world application, there would be additional code for user interfaces, testing, and deployment. Overall, Rollups offer several benefits that can help make the Ethereum network more efficient, scalable, and cost-effective, making them a promising solution for addressing the challenges facing the network. To make use of Rollups, leading organizations building with the technology also provide existing code examples, such as the Optimistic Rollup implementation from the , the implementation from , and implementation of their ZK-EVM. Optimism team ZK-Rollups Matter Labs Taiko Labs’ Comparison and Applications of Layer 2 Solutions Layer 2 scaling solutions such as state channels, Plasma, and Rollups are gaining traction amongst developers due to their ability to address the issues of high fees and slow transaction processing times on the Ethereum network. However, each solution has its own advantages and disadvantages, and you should carefully consider which approach is best suited for you based on their specific use cases. As a developer, it’s crucial to comprehend the technical distinctions between state channels, Plasma, and Rollups in order to determine the most appropriate Layer 2 solution for a specific use case. These solutions offer varying approaches to enhance the efficiency and scalability of the Ethereum network. allow users to open a channel between two parties on the mainchain, conducting multiple transactions without committing them to the blockchain immediately. State channels This approach greatly reduces gas costs and increases transaction throughput, making it suitable for use cases like micropayments for online content or services, such as pay-per-view videos, pay-per-use services like ride-sharing or bike-sharing, and gaming. However, the parties must be online and willing to sign transactions, and disputes can be expensive to resolve due to the need to go on-chain to do so. uses a sidechain to process transactions off-chain, reducing gas costs and increasing transaction throughput. It can support more complex smart contract functionality than state channels and is suitable for use cases that involve frequent but small transactions. Plasma Decentralized exchanges (DEXs) and gaming, where players can make in-game purchases or bet on game outcomes, are examples of use cases that can benefit from Plasma. However, users need to exit the sidechain to settle their funds on the mainchain, which can be time-consuming and costly. Additionally, the implementation of Plasma is still in active development, with multiple approaches being explored. use a smart contract on the mainchain to batch and verify transactions off-chain, achieving high levels of scalability while benefiting from the security and decentralization of the Ethereum network. Rollups They can support the same smart contract functionality as the mainchain, making them useful for use cases that require a high degree of security and decentralization. and decentralized exchange are examples of real-world applications of Rollups. Prediction market platform Augur Uniswap Users do not need to exit the mainchain to settle their funds, making it a more user-friendly option. However, implementing Rollups can be more complex than state channels or Plasma due to the need for additional infrastructure such as an aggregator, and the initial deposit required to use a Rollup can be high, making it less accessible to smaller users. Overall, the best Layer 2 solution for a given use case will depend on factors such as the types of transactions being conducted, the desired level of decentralization, and the level of complexity that can be tolerated. By carefully evaluating the strengths and weaknesses of each solution, you can choose the solution that best meets their needs. Conclusion To sum it up, Layer 2 solutions are crucial for the future of Ethereum. They offer a promising solution to enhance the scalability, efficiency, and usability of the network. This opens up new possibilities for various applications and use cases. Therefore, it’s important for developers and stakeholders in the Ethereum community to keep exploring and creating innovative solutions to ensure the network’s sustained progress and prosperity.

Scaling Ethereum: A Technical Overview of Layer 2 Solutions

Information is the foundation of good decision-making. Cryptocurrency innovates at the speed of light. New protocols are constantly coming to market, promising to solve some of mankind's greatest financial troubles. While their intentions might be good, the result is a cluttered, noisy environment that promotes FOMO & makes it nearly impossible to make sound decisions. In order to succeed in the wild, volatile, & often opaque world of cryptocurrency it is necessary to quiet the noise & hone in on real signals. The best way to do that is by building out your own Crypto ToolKit. Quick Notes on building a Crypto ToolKit: -) Do not use every single tool (unless you’re a crypto savant) -) Review each resource/tool individually (5–10 min per resource) -) Select only the ones that appeal most to your specific preferences As you might already be aware, the crypto-verse is highly fragmented in the sense that there are many different chains & protocols. Given that not all chains & protocols are interoperable (yet), all of the tools listed provided below are will be as general & multi-purpose as possible. Without further ado, Let's dive in: 📊 Market Data 📊 The starting point of almost every person’s crypto journey, Market Data providers are listing sites that aggregate all open financial digital asset data. All of the fundamental economic elements, Price, Volume, Circulating supply, Orderbooks, market dominance, historic data, & everything else. 1) Token Terminal - https://tokenterminal.com/ 2) Messari - https://messari.io/ 3) Crypto Slate - https://cryptoslate.com/coins/ 4) CoinGlass - https://www.coinglass.com/ Coin Market Cap -** 5) https://coinmarketcap.com/ - 6) Coin Gecko https://www.coingecko.com/ 7) Coin Metrics - https://coinmetrics.io/ 8) Coinlib - https://coinlib.io/ 9) Crypto Compare - https://www.cryptocompare.com/ 10) CoinCap - https://coincap.io/ - 11) CoinRanking https://coinranking.com/ 12) Coin360 — https://coin360.com/ — 13) Bitgur https://bitgur.com/ — 14) Nomics https://nomics.com/ - 15) CryptoWatch https://cryptowat.ch/ 16) BraveNewCoin — https://bravenewcoin.com/ 17) LiveCoinWatch — https://www.livecoinwatch.com/ 18) MultiCoinCharts - https://www.multicoincharts.com/home/ 19) Nansen - https://www.nansen.ai/ 20) CoinPaprika - https://coinpaprika.com/ 21) CoinAlpha - https://coinalpha.app/ 22) CoinScope - https://www.coinscope.co/ 23) DropsTabs - https://dropstab.com/ 24) CryptoView - https://www.cryptoview.com/ 25) CoinCarp - https://www.coincarp.com/ 26) Mytokencap - https://www.mytokencap.com/ 27) CoinCodex — https://coincodex.com/ — 28) CoinLobster https://coinlobster.com/ 💱 DEFI Dashboard & Aggregators💱 Decentralized finance is an incredibly broad term that includes a wide range of applications that vary based on functionality & intended purpose. While the majority of current DEFI activity happens across 4 blockchains (Ethereum, Binance Smart Chain, Polygon & Solana) there are so many up & coming alternative platforms such as Optimism & Arbitrum that have been garnering attention that for the sake of brevity I will only list the few products that I am personally familiar with. 1) Dapp Radar — https://dappradar.com/defi 2) DEFI Llama — https://defillama.com/ 3) DEFI Prime — https://defiprime.com/ 4) DEFI Pulse — https://www.defipulse.com/ 5) YieldWatch - https://www.yieldwatch.net/ 6) ZapperFI - https://zapper.xyz/ 7) Zerion - https://zerion.io/ 8) InstaDapp - https://instadapp.io/ 9) Frontier - https://www.frontier.xyz/ 10) Apebored - https://apeboard.finance/ 11) Debank - https://debank.com/ - 12) APYvision https://app.apy.vision/ - 13) Plasma Finance https://plasma.finance/ - 14) Farm Army https://farm.army/ - 15) DEFISaver https://defisaver.com/ - 16) Gnosis Safe https://gnosis-safe.io/ - 17) DefiYield https://defiyield.app/ 18) Coin98 - https://coin98.com/ 19) AstroTools - https://astrotools.io/ 20) MultiFarm - https://www.multifarm.fi/ 21) OctoFi - https://octo.fi/ 22) Parallel - https://parallel.fi/ 23) Exponential - https://exponential.fi/ 24) WalletDefi - https://walletdefi.app/ 25) DEFImarketCap - https://defimarketcap.io/ 26) QuantifyCrypto - https://quantifycrypto.com/ 📰 News 📰 Crypto is becoming all the more politicized as time goes on. An absurd amount of crypto/DEFI news sites pop up constantly & push their own agendas. The best way to source news (in any industry) is by having a few reliable individual outlets & cross-referencing information across them all. 1) CoinDesk - https://www.coindesk.com/ 2) Coin Telegraph - https://cointelegraph.com/ 3) Bitcoin Magazine - https://bitcoinmagazine.com/ 4) The Cryptonomist - https://en.cryptonomist.ch/ 5) Be In Crypto - https://beincrypto.com/ 6) CoinGape - https://coingape.com/ 7) CryptoSlate - https://cryptoslate.com/ 8) Crypto Briefing - https://cryptobriefing.com/ 9) CryptoDaily - https://cryptodaily.co.uk/ 10) Crypto Potato - https://cryptopotato.com/ 11) BraveNewCoin - https://bravenewcoin.com/ 12) Coin Journal - https://coinjournal.net/ 13) Coin Speaker - https://www.coinspeaker.com/ 14) CoinCu - https://news.coincu.com/ 15) Bitcoinist - https://bitcoinist.com/ 16) CryptoPanic - https://cryptopanic.com/ 17) Crypto News - https://cryptonews.com/ 18) U Today - https://u.today/ 19) CoinGraph - https://www.coingraph.news/ - 20) Decrypt https://decrypt.co/ - 21) Blockworks https://blockworks.co/ - 22) CryptoCapitalNews https://cryptocapitalnews.com/ — 23) Protos https://protos.com/ 👛 Wallets 👛 Wallets are the foundation for getting involved & staying in crypto. Wallets are exactly what they sound like, places to securely store/view your crypto asset holdings. Wallets typically come in 2 flavors, Chain-specific & Chain-agnostic. Chain-specific wallets are tied to a single blockchain platform (i.e ETH/BNB). These will only be able to store their native chain tokens, but allow the users to interact with on-chain assets/applications. Whereas chain-agnostic wallets might allow their users to store crypto assets from any blockchain, but that is the limit of their capabilities as they are usually single-purpose only (storage) 1) MetaMask - https://metamask.io/ 2) MEW - https://www.myetherwallet.com/ 3) Dynamic - https://www.dynamic.xyz/ 4) XDEFI - https://www.xdefi.io/ 5) Enkryptic - https://www.enkrypt.com/ 6) Argent - https://www.argent.xyz/ 7) Dopamine - https://dopamineapp.com/ 8) TrustWallet - https://trustwallet.com/ 9) Eidoo - https://eidoo.app/ 10) Dapppocket - https://www.dapppocket.io/ 11) Atomic Wallet - https://atomicwallet.io/ 12) Bread Wallet - https://brd.com/ 13) Guarda - https://guarda.com/ 14) Exodus - https://www.exodus.com/ 15) ZenGo - https://zengo.com/ 16) Coinomi - https://www.coinomi.com/en/ 17) Luno - https://www.luno.com/en-US 18) Ambire - https://www.ambire.com/ 19) Jaxx - https://jaxx.io/ 20) Edge - https://edge.app/ 21) Freewallet - https://freewallet.org/ 22) Coinbase Wallet - https://www.coinbase.com/wallet 23) Coin Wallet - https://coin.space/ 24) Ballet Wallet - https://www.ballet.com/coins/ 25) Unstoppable - https://unstoppable.money/ 26) Brave Wallet - https://brave.com/wallet/ 27) BitPay - https://bitpay.com/wallet/ 28) Crypto.com - https://crypto.com/us/defi-wallet 🔎 Explorers 🔍 Explorers are software tools that allow users to inspect the activity that has happened/is happening on-chain. Explorers are typically built-to-blockchain, meaning every chain needs its own explorer. Given the girth of data these tools access, explorers tend to be multi-purpose tools (i.e. data providers/ analytics dashboards/compliance). 1) Ethscan - https://etherscan.io/ 2) Bitquery - https://explorer.bitquery.io/ 3) Blockchair - https://blockchair.com/ 4) Tokenview - https://tokenview.io/ 5) Blockcypher - https://www.blockcypher.com/ 6) GetBlock - https://getblock.io/explorers/ 7) ViewBlock - https://viewblock.io/ - 8) BreadCrumbs https://www.breadcrumbs.app/ 9) Beaconchain - https://beaconcha.in/ 10) Blockstream - https://blockstream.info/ 11) Ethplorer - https://ethplorer.io/ 12) OXT - https://oxt.me/ 13) Xscan - https://xscan.io/ 14) Sochain - https://sochain.com/ 15) OkLink - https://www.oklink.com/en 16) Pingpub - https://ping.pub/ ⛓ On-Chain Data ⛓ On-chain data tools are closely related to explorers in the sense that they allow users to inspect the activity that has happened / is happening on-chain. The main difference between the On-chain Data tools & Explorers is the UI & granularity of data they provide.*The main difference between On-Chain data providers & traditional market data is the absence of information that is external to any blockchain. 1) Glassnode - https://glassnode.com/ 2) Dune Analytics - https://dune.com/home 3) IntoTheBlock - https://www.intotheblock.com/ - 4) Mempool https://mempool.space/ 5) Artemis - https://www.artemis.xyz/ - 6) Parsiq https://www.parsiq.net/ 🌉 Bridges 🌉 Within the context of cryptocurrency, a bridge is a software tool or protocol that allows otherwise non-compatible blockchains a method to transfer digital assets between one another. 1) MultiChain - https://multichain.org/ 2) CrossChain Bridge - https://www.crosschainbridge.org/ 3) Celer C Bridge - https://cbridge.celer.network/1/56/USDC 4) Synapse - https://synapseprotocol.com/ 5) Connext - https://bridge.connext.network/USDC-from-ethereum-to-binance 6) Relay - https://www.relaychain.com/ 7) Symbiosis - https://symbiosis.finance/ 8) Umbria - https://umbria.network/ 9) EverBridge - https://www.everrise.com/everbridge/ 10) Bungee - https://www.bungee.exchange/ 11) Portal Bridge - https://www.portalbridge.com/#/transfer 12) Nomad - https://www.nomad.xyz/ 13) Hop - https://hop.exchange/ 14) PolyBridge - https://bridge.poly.network/ 15) SolarBeam - https://app.solarbeam.io/bridge 16) Orbitchain - https://orbitchain.io/about 💹 DEXes 💹 Decentralized Exchanges are the new financial trading paradigm. Generally free from traditional regulatory scrutiny, DEXs are places to buy, sell, swap & provide liquidity for crypto assets. 1) UniSwap - https://uniswap.org/ 2) 1inch - https://app.1inch.io/ 3) DexTools - https://www.dextools.io/app/en 4) DexGuru - https://dex.guru/ 5) GeckoTerminal - https://www.geckoterminal.com/ 6) PancakeSwap - https://pancakeswap.finance/ 7) TraderJoe - https://traderjoexyz.com/avalanche 8) Arken - https://swap.arken.finance/ 9) Flooz - https://flooz.trade/trade 10) Balancer - https://balancer.fi/ 11) Bancor - https://home.bancor.network/ 12) Airswap - https://www.airswap.io/#/ - 13) Sushiswap https://www.sushi.com/ 14) Paraswap - https://www.paraswap.io/ 15) Jupiter - https://jup.ag/ 16) ThorChain - https://thorchain.org/ 17) WooFi - https://fi.woo.org/ 18) DYDX - https://trade.dydx.exchange/ - 19) Slingshot https://app.slingshot.finance/swap/ETH 20) Apex Exchange - https://www.apex.exchange/ 21) Osmosis - https://app.osmosis.zone/ 22) Curve - https://curve.fi/#/ethereum/swap 23) Tokenlon - https://tokenlon.im/instant 24) Swapz — https://www.swapz.app/ 📅 Calendars & Event Schedules 📅 Keeping up with the Kardashians is much easier than keeping up with your favorite crypto protocol; the question then becomes HOW do you plan to manage the onslaught on events? While there is no easy answer, using a Crypto Calander will definitely help: 1) CoinMarketCal - https://coinmarketcal.com/en/ 2) CoinDar - https://coindar.org/ 3) CoinsCalendar - https://coinscalendar.com/ 4) CryptoTotem - https://cryptototem.com/ico-calendar/ 5) CoinCarp events - https://www.coincarp.com/events/ 6) VestLabs - https://vestlab.io/calendar 🪂 Airdrops 🪂 The most popular tool for distribution in the entire industry, airdrops are incentives that are offered/provided at the earlier stages of a project’s development to help bootstrap it’s alpha community members. 1) Earnifi - https://earni.fi/ 2) airdropsio - https://airdrops.io/ 3) AirDropAlert - https://airdropalert.com/ 4) AirdropsLive - https://airdrops.live/ 5) AirdropBob - https://www.airdropbob.com/ 6) AirDropAddict - https://airdropaddict.com/ 7) CoinAirDrops - https://coinairdrops.com/ 8) ICOdrops - https://icodrops.com/ 💸 Grants 💸 Grants are a necessary component to helping startups & innovators get their ideas off the ground. In the world of crypto & blockchain grants are usually offered & deployed on a chain/case-specific basis. In order to be properly up to date on grant opportunities it is best to be actively involved in individual projects and/or blockchains. 1) Blockchain Grants - https://www.blockchaingrants.org/ 2) GitCoin - https://gitcoin.co/grants/ 3) Consensys - https://consensys.net/grants/ — 4) Concoridum https://concordium.com/grants/ 5) Web3 grants - https://web3grants.net/ 6) Web3Foundation - https://web3.foundation/grants/ 7) Ramp Rate - https://ramprate.com/blockchain-grant-opportunities/ - 8) Unigrants https://www.unigrants.org/ 9) Aave grants - https://aavegrants.org/ 10) Near grants - https://near.org/ecosystem/get-funding/ 11) Eth Foundation - https://esp.ethereum.foundation/ 12) Zcash grants - https://grants.zfnd.org/ 13) Alchemy Dev grants - https://www.alchemy.com/developer-grant-program — 14) dydx grants https://www.dydxgrants.com/ 15) Solana grants — https://solana.org/grants 16) Gate grants - https://www.gate.io/grants 17) Cryptoneur - https://www.cryptoneur.xyz/en/web3-grants 🛡 Audits 🛡 Audits are used to assess the quality/security of a protocol. When considering a protocol to use, it is nearly impossible to understand all of the associated risk factors, even for professionals. It is crucial that every serious project employs some form of audit for every individual piece of software. 1) Certik - https://www.certik.com/ 2) Consensys Dilligence - https://consensys.net/diligence/ 3) Hacken - https://hacken.io/services/smart-contract-security-audit/ 4) Open Zepplin - https://www.openzeppelin.com/security-audits 5) Trail of Bits - https://www.trailofbits.com/ 6) Slowmist - https://www.slowmist.com/ 7) Solidified - https://solidified.io/ 8) Chain Security - https://chainsecurity.com/smart-contract-audit-reports/ 9) PeckShield - https://peckshield.com/#home 10) Halborn - https://halborn.com/ 11) Quantstamp - https://quantstamp.com/ 12) Solidity Finance - https://solidity.finance/ - 13) Immune Bytes https://www.immunebytes.com/ 14) NumenCyber - https://www.numencyber.com/ 🌊😎 Cool & Honorable Mentions 😎🌊 There are always exotic instruments & services being built to help make sense of the wild world of crypto; some of these are difficult to classify but still deserve attention for serving their own unique & useful purpose(s). 1) Fiat Leak - https://fiatleak.com/ 2) Everest - https://everest.link/ 3) Revoke.cash - https://revoke.cash/ 4) CryptoQuant - https://cryptoquant.com/asset/btc/summary - 5) CryptoFees https://cryptofees.info/ - 6) Hashrate Index https://data.hashrateindex.com/asic-index-data — 7) LunarCrush https://lunarcrush.com/home — 8) Santiment https://santiment.net/ 9) Gas Fee Calculator - https://www.cryptoneur.xyz/en/gas-fees-calculator This list is by no means exhaustive, there are thousands of other tools/resources out there. Odds are, you do not even need 1/10 of those on this list; so my recommendation is don’t waste time wishing for better tools — learn how to masterfully use a few key ones provided above. If you went through the entire list, you might have noticed that there are no CEFI (centralized financial) tools on this list. This was done on purpose, given the madness that transpired with centralized exchanges/service providers throughout 2022. If you would like me to add any specific resource that might be beneficial to others, just drop a comment below or send me a DM on Twitter. Otherwise; I hope you find these tools helpful in building your knowledge & financial freedom. Thank you so much for reading! 🥂🚀 See you in the next Bull Market 🚀🥂 Also published here.

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In this post, we’d like to share 10 useful Python tips and tricks for beginners with you. Python is one of the most for data scientists. Besides providing a free for beginners, we also summarize these 10 tips and tricks, which should help you with daily data science tasks. in-demand skills Python course Following this beginners’ tutorial, you’ll learn how to: format strings use enumerate, sorted functions return multiple values from a function use lambda expression, list comprehensions Lots more! If you want to make your Python coding more efficient, don’t miss these tips/tricks! Let’s begin. Tip #1: Display Methods/Functions With Python being so powerful, there are many different methods and functions. It’s especially hard for beginners to memorize all. How do we find out the available methods/functions for a Python object? The first Python tip for beginners is about two quick ways of doing this. Method #1: Code completion feature Many IDEs (Integrated Development Environment) or code editing applications for Python can auto-complete the code while you are typing. This feature is helpful to speed up programming. For example, within Jupyter Notebook, you can type in the first few characters of a function/files, etc., and then press the key to fill in the rest of the item. The screenshot below shows the available autocomplete options that start with the letter ‘p’. Tab Method #2: dir function The function returns a list of valid attributes for the object in its argument, which means we can use it to return an object’s methods. dir For example, let’s run the below Python code to apply dir on a string object. s = print(dir(s)) 'a string' This will return a long list of names. Ignoring those special methods with ‘__’ at the beginning of the list, you can find interesting methods such as capitalize, find, and lower. ['__add__', '__class__', '__contains__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getitem__', '__getnewargs__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__iter__', '__le__', '__len__', '__lt__', '__mod__', '__mul__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__rmod__', '__rmul__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'capitalize', 'casefold', 'center', 'count', 'encode', 'endswith', 'expandtabs', 'find', 'format', 'format_map', 'index', 'isalnum', 'isalpha', 'isascii', 'isdecimal', 'isdigit', 'isidentifier', 'islower', 'isnumeric', 'isprintable', 'isspace', 'istitle', 'isupper', 'join', 'ljust', 'lower', 'lstrip', 'maketrans', 'partition', 'replace', 'rfind', 'rindex', 'rjust', 'rpartition', 'rsplit', 'rstrip', 'split', 'splitlines', 'startswith', 'strip', 'swapcase', 'title', 'translate', 'upper', 'zfill'] : only provides an interesting set of names more than a full list. But it’s convenient to use when you can’t recall a method that you are aware of. Note dir Besides dir, you can also try the function. For example, help(str) will print out the Help page on the string object, which contains more details of the methods than dir. help Tip #2: Format Strings Printing out strings is a common task within data science projects. The method of str can piece multiple variables and strings together and format them in specific ways. format Let’s see an example. We’ll define three variables , , and (=paid — price). What if we want to print out a full sentence containing these variables formatted as dollars? price paid change We can use the format method as below. price = * paid = change = paid - price
print( .format(price, paid, change)) 9.99 1.13 20 'The item cost ${0:,.2f}. I paid ${1:,.2f}. I received ${2:,.2f} in change' The item cost $11.29. I paid $20.00. I received $8.71 in change Tip #3: Enumerate Function When iterating over an object such as a list, dictionary, or file, is a useful function. The function returns a tuple containing both the values obtained from iterating over the object, and the loop counter (from the start position of 0). The loop counter is especially handy when you want to write code based on the index. enumerate Let’s see an example where we can do something special for the first and last element. lst = length = len(lst) i, element enumerate(lst):
    print( .format(i, element)) i == :
        print( ) i == length - :
        print( ) 'Just Into Data' for in '{}: {}' if 0 'The first element!' elif 1 'The last element!' We printed strings indicating the first and the last element conveniently with enumerate. 0: J The first element! 1: u 2: s 3: t 4: 5: I 6: n 7: t 8: o 9: 10: D 11: a 12: t 13: a The last element! The enumerate function can also be used on files. In the example below, we can print out the first 10 rows of the csv file before breaking out of the loop. We won’t copy the result here since it’s too long. But you can try it on any files you have. open( ) f: i, line enumerate(f): i == : print(line) with 'sberbank.csv' as for in if 10 break Tip #4: Return Multiple Values in a Function When defining functions, we often want to return more than one value. In this Python tip/trick, we’ll cover three common methods below. Method #1: Return a Tuple First, let’s look at the most convenient way: returning a tuple. We usually only use this method if there are 2 or 3 values to return. When the number of values is more, it’s easy to forget about the order of the values within the tuple. Below is an example function get_employee, which returns the employee’s first and last name as tuples, based on their ID numbers. id_num == : , id_num == : , : Exception( .format(id_num)) # returning a tuple. : def get_employee (id_num) if 0 return 'Jane' 'Doe' elif 1 return 'John' 'Smith' else raise 'No employee with this id: {}' If we call the function with value of 0, you can see that the function returns the tuple with two values: ‘Jane’ and ‘Doe’. employee = get_employee( )
print( .format(employee[ ], employee[ ])) 0 'first_name: {}, last_name: {}' 0 1 first_name: Jane, last_name: Doe This is great, but what should we do when there are more values to return? Let’s move on to the next method. Method #2: Return a Dictionary The second way is to return a dictionary. Dictionaries can be thought of as key: value pairs, so we can name the values that are returned, which is more clear than tuples. The example below is similar to the previous one. But we ask the function to return a dictionary. id_num == : { : , : , : , : , : } id_num == : { : , : , : , : , : } : Exception( .format(id_num)) # returning a dictionary : def get_employee (id_num) if 0 return 'first_name' 'Jane' 'last_name' 'Doe' 'title' 'Data Scientist' 'department' 'A' 'date_joined' '20190808' elif 1 return 'first_name' 'John' 'last_name' 'Smith' 'title' 'Data Engineer' 'department' 'B' 'date_joined' '20190808' else raise 'No employee with this id: {}' We can call the function with id_num = 0. With the result as a dictionary, it’s easier to call the specific value with its key. employee = get_employee( )
print( .format(
    employee[ ], employee[ ], employee[ ], employee[ ], employee[ ])) 0 'first_name: {},\nlast_name: {},\ntitle: {},\ndepartment: {},\ndate_joined: {}' 'first_name' 'last_name' 'title' 'department' 'date_joined' first_name: Jane, last_name: Doe, title: Data Scientist, department: A, date_joined: 20190808 Method #3: Return a NamedTuple The last way we’ll discuss is returning a namedtuple. The named tuples are tuples with named fields. They are immutable like tuples, but also provide naming like dictionaries. Named tuples assign meaning to each position in a tuple and allow for more readable, self-documenting code. They can be used wherever regular tuples are used, and they add the ability to access fields by name instead of position index. Python docs The main advantage named tuples have over dictionaries is that the fields are guaranteed to be in the object. With a dictionary, we’re not sure if all the key: value pairs will be there. Let’s see an example of the named tuple. We have to define the namedtuple object before using it. In the code below, we created a namedtuple object called , and then used it to hold values. Employee collections
Employee = collections.namedtuple( , [ , , , , ]) id_num == : Employee(first_name= , last_name= , title= , department= , date_joined= ) id_num == : Employee(first_name= , last_name= , title= , department= , date_joined= ) : Exception( .format(id_num)) # returning a namedtuple. import 'Employee' 'first_name' 'last_name' 'title' 'department' 'date_joined' : def get_employee (id_num) if 0 return 'Jane' 'Doe' 'Data Scientist' 'A' '20190808' elif 1 return 'John' 'Smith' 'Data Engineer' 'B' '20190808' else raise 'No employee with this id: {}' We can call the function again with id_num = 0 to return the named tuple. employee = get_employee( )
print( .format(
    employee.first_name, employee.last_name, employee.title, employee.department, employee.date_joined)) 0 'first_name: {},\nlast_name: {},\ntitle: {},\ndepartment: {},\ndate_joined: {}' first_name: Jane, last_name: Doe, title: Data Scientist, department: A, date_joined: 20190808 We can also double check the variable type of the returned object, which is the Employee namedtuple defined earlier. type(employee) __main__.Employee Tip #5: Lambda Expression The are used to create anonymous functions, which are usually single-line. Lambda expressions Below is an example showing how lambda can shorten the code for creating simple functions. pandas pd
df = pd.DataFrame(data={ : [ , , , , , ]}) address.split()[ ].lower()

df[ ].map(get_streetname) df[ ].map( address: address.split()[ ].lower()) import as 'address' '12 first St' '15 Second St' '20 ThIRd St' '2 First St' '8 THIRD St' '100 fIRST st' # without lambda. : def get_streetname (address) return 1 'address' # using lambda function. Shorter and more clear. 'address' lambda 1 Both methods return the same result below. 0     first 1    second 2     third 3     first 4     third 5     first Name: address, dtype: object Tip #6: Sorted Function We’ll cover the useful function for this Python tip, with examples of lists and dictionaries. It’s a common task since we often want to see the top/bottom values in a dataset. sorted Sort Lists Let’s look at a simple example for a list using the sorted function. lst = [ , , , , , ]

sorted_lst = sorted(lst)
sorted_lst 5 5 3 8 1 9 [1, 3, 5, 5, 8, 9] : there’s also the list.sort() method, but we prefer sorted since it’s more general and creates a new list. See more detailed comparisons in the . Note Python docs Sort Dictionaries For dictionaries, sorting is a little more complicated since there are keys and values. We can apply the sorted function directly to the dictionary, which will sort the dictionary’s keys. d = { : , : , : , : , : }
sorted(d) # Get the keys in sorted order. 'T' 3 'Q' 7 'A' 9 'G' 0 'B' 8 ['A', 'B', 'G', 'Q', 'T'] Or sort the values of the dictionaries as below. d = { : , : , : , : , : }
sorted(d.values()) # Get the values in sorted order. 'T' 3 'Q' 7 'A' 9 'G' 0 'B' 8 [0, 3, 7, 8, 9] Or sort the whole dictionaries by either its keys or values in the Python code below. {k:v k,v sorted(d.items())} {k:v k,v sorted(d.items(), key= it: it[ ])} # sort the dictionary by key. for in # sort the dictionary by value. for in lambda 1 {'A': 9, 'B': 8, 'G': 0, 'Q': 7, 'T': 3} {'G': 0, 'T': 3, 'Q': 7, 'B': 8, 'A': 9} Tip #7: Conditional Expressions If you’ve learned the basics of Python, you should be familiar with the if-else statements. When the logic is simple, we can also use the (or ternary operator) in one line. conditional expression Let’s see an example based on the below boolean variable is_raining. is_raining = True The Python code below shows the traditional way of doing it. is_raining:
    action = :
    action = print(action) if 'Stay at home' else 'Go for a walk' Stay at home Yet, we can also use the expression below. It’s much shorter! The expression x if C else y first evaluates the condition, C rather than x. If C is true, x is evaluated and its value is returned; otherwise, y is evaluated and its value is returned. Python docs action = is_raining print(action) 'Stay at home' if else 'Go for a walk' Tip #8: List Comprehensions We can create lists using list comprehensions, which is much more compact than the traditional method. It’s commonly used when each element of the new list results from some operations on the element of another iterable object. A list comprehension consists of brackets containing an expression followed by a clause, then zero or more or clauses. The result will be a new list resulting from evaluating the expression in the context of the and clauses which follow it. for for if for if Python docs The example shows how to use it counting the length of words in a string and assign the result as a list. cat_in_the_hat = len_list1 = [] s cat_in_the_hat.split():
    len_list1.append(len(s)) len_list2 = [len(s) s cat_in_the_hat.split()]

print(len_list1)
print()
print(len_list2) """the sun did not shine.
it was too wet to play.
so we sat in the house
all that cold, cold, wet day.
i sat there with sally.
we sat there, we two.
and i said, 'how i wish
we had something to do!'
too wet to go out
and too cold to play ball.
so we sat in the house.
we did nothing at all.
so all we could do was to
sit!
sit!
sit!
sit!
and we did not like it.
not one little bit.""" # assume we want to count the length of each word in the string. # long way. for in # using list comprehensions we can do this in one line. for in Both methods return the same results below, while the list comprehension code being much shorter. [3, 3, 3, 3, 6, 2, 3, 3, 3, 2, 5, 2, 2, 3, 2, 3, 5, 3, 4, 5, 5, 3, 4, 1, 3, 5, 4, 6, 2, 3, 6, 2, 4, 3, 1, 5, 4, 1, 4, 2, 3, 9, 2, 4, 3, 3, 2, 2, 3, 3, 3, 4, 2, 4, 5, 2, 2, 3, 2, 3, 6, 2, 3, 7, 2, 4, 2, 3, 2, 5, 2, 3, 2, 4, 4, 4, 4, 3, 2, 3, 3, 4, 3, 3, 3, 6, 4] Tip #9: All/Any Functions We’d also like to cover the and the functions in Python. They are convenient when making multiple comparisons. all any The any function returns True if any element of an iterable object is true. The example below shows how it makes coding more straightforward. my_string = my_string my_string my_string my_string my_string:
    print(my_string) any([c my_string c [ , , , , ]]):
    print(my_string) 'Toronto, Ontario' # the long way. if 'Montreal' in or 'Toronto' in or 'Vancouver' in or 'Boston' in or 'New York' in # use the any function # this way is shorter than the previous way. if in for in 'Montreal' 'Toronto' 'Vancouver' 'Boston' 'New York' Toronto, Ontario Similarly, the all function returns True if all elements of an iterable object are true (or if the iterable is empty). Below is an example to compare the all function and the usual method. my_string2 = my_string2 my_string2 my_string2:
    print(my_string2) all([c my_string2 c [ , , ]]):
    print(my_string2) 'Just Into Data' # the usual way if 'Just' in and 'In' in and 'Data' in # use all function if in for in 'Just' 'Into' 'Data' Just Into Data Tip #10: Use Virtual Environments If you are working on multiple data science projects at once, it’s critical to learn and use virtual environments. What are the virtual environments for Python? A virtual environment is a Python environment such that the Python interpreter, libraries and scripts installed into it are isolated from those installed in other virtual environments, and (by default) any libraries installed in a “system” Python, i.e., one which is installed as part of your operating system. Python docs You can create and manage virtual environments using tools like , , . Anaconda (conda environments) virtualenv pipenv Virtual environments allow different Python environments for each project, so that we can use different versions of Python and/or sets of libraries. For example, let’s say we used plotly version 3 to create charts in a project. After a few months, plotly version 4 came out with new features. Since the project’s code had been working well in production, we are good to continue using Plotly version 3. But for any new projects, we’d like to use the new features in Plotly version 4. In this situation, we can create two virtual environments with plotly v3 and v4 separately, and use them for the old and new projects. Problems solved! That’s it! Hope you found these Python tips and tricks for beginners useful. Which tip from this post do you want to try first? Leave a comment for any questions you may have or anything else. : Related resources For beginners of Python, check out our pandas and numpy tutorials to continue learning: Learn Python Pandas for Data Science: Quick Tutorial Python NumPy Tutorial: Practical Basics for Data Science Or check out our other recent data science for beginners articles: 7 steps to a successful Data Science Pipeline Machine Learning for Beginners: Overview of Algorithm Types For more useful data science articles, ! sign up our newsletter

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