關於 voila教學 ，我們在網路上蒐集到這些相關的討論、資訊與評價

【神秘的維修工坊】

幾個月前，Bruno河馬萬用電鍋在一次過熱意外中陷入昏迷，Melody從朋友那聽說市區有間每個月只開兩小時的神秘維修工坊（Repair Cafe)，任何家電產品都是壞的進去，都能生龍活虎地出來。

我們帶著忐忑的心情，按下了門鈴。

「請問這裡是維修工坊嗎？」
「是的，我們正準備開始，歡迎。」接待人員領著我們到一間明亮的工作室，一位灰髮的爺爺工匠正在研究著一個被分解的二氧化碳檢測儀。
嗶嗶嗶⋯⋯！
「嗯，這個面板不行了。我等等看看倉庫有沒有材料。喔哈囉，我叫葛蘭。你們今天帶來什麼挑戰？」雖然隔著口罩，還是能感覺到他咧嘴微笑著。

我把死河馬輕輕地平放在工作台上，葛蘭驚艷的讚嘆聲引來了室內的所有人。

「哇，這是⋯⋯什麼寶貝？」
死河馬。

「這是一台萬用電鍋，它可以用來煮火鍋、壽喜燒、鬆餅⋯⋯」Melody開啟銷售模式。
欸，我們是來修東西不是來賣東西的。

我用anyways打斷她，「我們有次不小心地讓機器過熱，然後它就昏迷不醒了。」

「來看看它到底怎麼了吧！」葛蘭躍躍欲試地捲起袖子，在一旁修燈座的電工和正在幫人造火爐量背板的木工師傅露出羨慕的眼光，在正式開始維修前，他們還輪流把玩了一下Bruno的磁力插座。

「這設計好酷喔！」師傅們喀噠喀噠地插拔著插座，Ophelia也湊熱鬧玩了兩次。

葛蘭從口袋拿出一個電壓測試器，紅黑兩條感應針在各個通電口上戳來戳去。
本以為我們只要站在一旁等著葛蘭修河馬就好，沒想到葛蘭翻轉研究河馬一番後，便將螺絲起子交給我。
「把這些螺絲釘拆掉吧。」他指著銀色導熱板邊上的四角。
我照做，然後掀開不再受阻礙的板架。
原來內部構造這麼⋯⋯單調啊？
河馬內部只有幾條紅黑火線，然後原來溫度調節軸不過是個把加熱板上下推動的簡約設計。

「Bruno原來是賣品牌的啊？」我脫口而出。
「但是很好用啊！」Melody護航。
也是。確實好用。

葛蘭很快就發現問題，黑色火線是通的，但是紅色火線卻不存在交流反應。
「找到問題了。」葛蘭手指順著紅線，「嗯？這裡分岔了。」紅線一端分支成兩段，一端接入加熱器，另一端接著顯示燈。分支的結構被絕緣膠管刻意掩蓋。
他拉開膠管，然後：「Voila！」他找到答案了。
一根溫度保險絲（Thermal fuse）。
「肯定是它了！」

接下來就是枯燥的拆解、嘗試、討論、安裝、再嘗試的過程。
每一個環節葛蘭都要求我和Melody參與，自己的河馬自己修。

「好，拿去通電試試看吧！」
葛蘭將電源向右扳，橘燈亮起。
「it’s alive！」大家歡呼起來！
河馬復活了！

復活後的河馬加熱速度超快，為了等它冷卻，葛蘭帶著我們參觀工坊。

原來這間神秘的維修工坊是個寓教於樂的場所，另一個房間內充滿了各式各樣我能形容但交不出專有名詞的重型機械。

雕刻柱子的機器、製作混合木板的機器、切割鋼鐵的圓鋸、水雕機、3D列印機、用電館加熱鐵管然後冶鐵的機器和巨大塑形用的板⋯⋯

通常使用這個工坊是需要付月費的，據說葛蘭的所有傢俱都是自己從這裡做出來的。

許多人都會來這施展身手。

上個月有人才完成了一個queen size的上下舖。
目前待完成的項目包括餐桌、躺椅、木吉他、搖籃還有獨木舟。

「有興趣的話，維修工坊每個月的最後一個星期四都會開放維修教學，下個月準備帶什麼壞掉的寶物來修呢？」葛蘭問。
「他。」Melody指著我。
「哈哈哈⋯⋯可能修不好囉？」葛蘭開懷地捧腹大笑。

#yukonstruct
#現在可以一次用兩台Bruno了
#小魔頭與貓媽熊爸

#MealKit評測

最近沈浸在meal kit的小小天地裡，不僅紙上談兵，也動手實作。

繼前幾週嘗試了Gen Creative、Club Voila和Solo Pasta後，本週繼續實驗Studio Kyu Kyu「手工披薩DIY組合」、logy「Spaghetti alla Carbonara 培根起司蛋麵」、FoodGo Box「經典威靈頓牛排」與「香色那可那可雞」，我簡直，meal kit開箱達人（自己講）。

各位沒有走錯棚，這裡不是婦仇者廚房。

#StudioKyukyu #在家做披薩

Studio Kyu Kyu是由日籍主廚萩本郡大（Kunihiro Hagimoto）與太太Joyce一起創立的烹飪教室。如果大家有印象，在義大利摘米其林星的德吉洋二主廚三年多前曾在台北101開設快閃餐廳「TABLE by Yoji Tokuyoshi」，當時被派駐在台北的就是萩本主廚，人稱Kuni桑。半年的客座經歷也讓他種下緣分，去年成了台灣女婿。

疫情中烹飪教室也無法營業，該如何變通？擅長義大利菜的Kuni主廚研發出披薩DIY組，讓人買回家自己做披薩，厲害在於，就算使用家用烤箱，也能做出媲美餐廳窯烤的拿坡里披薩。拿坡里披薩的烤窯溫度高達攝氏430度至480度，只消數十秒就能烤出酥香帶焦痕的餅皮，家用烤箱最高溫不過攝氏250度，怎麼辦到？Kuni主廚想出偷吃步：先用平底鍋煎脆餅皮，用噴槍加工烈焰焦香，再進家用烤箱。

可是家裡沒有噴槍啊？安啦，跳過跳過。

DIY組含二個麵團、二種口味的配料：瑪格麗特與芝麻葉帶皮火腿，一紅一白，相當貼心。除了文字說明，掃QR code也能連上教學影片，Kuni主廚隔著螢幕手把手教，還附上緊急聯絡電話（！）。

我想我是該打通電話過去的。我的麵糰，從整型就是災難......不知是否因為在冰箱多待了一天，白拋拋的麵糰，太幼咪咪了，我無法掌握，濕黏不聽話，我又從沒操作過麵糰，第一顆勉強完成，第二顆擺爛攤軟，不管了，就放進盒子發酵......四小時後，它還是爛泥，只是變比較大灘而已...

硬著頭皮繼續做，不然沒晚飯吃。把餅皮用手指壓開，然後，就破了......沒事，塗上番茄醬汁，擺上莫札瑞拉遮起來。再把餅皮滑進放了油的平底鍋裡煎，這一步，就是仆街，餅皮翻滾折半，醬汁到處亂流，哈哈哈哈。

烤箱不會拒絕醜醜的披薩入內。

神奇的是，即便多災多難，奇形怪狀，這披薩，味道還不賴。餅皮鬆化輕盈，平底鍋煎脆是好招，Kuni主廚熬的番茄醬鮮活有味，和羅勒、莫札瑞拉攜手拯救了我的晚餐。白色的瑞可達、帶皮火腿、芝麻葉也好吃，搭上Kuni主廚的秘方—糖漬檸檬皮，清亮芳香。起司當然都是「慢慢弄」的。

後來才知道，Kuni主廚的麵糰含水量達80%，所以不好操作。也因為含水量高，這披薩才能外酥內鬆，咀嚼間也透出麥香。

看了我的作品後，相信大家都信心滿滿。

💡評測心得：
不需要把這披薩DIY組當作快速上菜的救星。它適合家人一起動手勞作，在悠閒的週末，花點時間和麵粉、酵母、親子夫妻相處。

#logy #把煮義大利麵說清楚

做披薩不簡單，煮義大利麵總輕鬆寫意了吧？

醬汁還幫你調好了耶。

logy 的田原諒悟主廚，在餐廳休息的期間一直在想他能為客人做什麼。蹦出來的產品是，從餐廳精緻菜色改弦易轍的，輕鬆方便的義大利麵懶人包，且是他很有感情的一道義麵— 培根起司蛋麵（Spaghetti alla Carbonara）。「這裡面不要加鮮奶油喔」，田原主廚永遠記得在廚藝學校裡義大利主廚的正確示範，如何顛覆印象，他又如何在極簡的食材中追求火侯的掌控與比例的平衡。他說，這道麵「濃縮了我過去十八年來的經驗」。

米其林二星餐廳推出單價一千元、四人份的義麵meal kit，預訂浪潮瞬起，開放訂單二天後就得關閉，否則做不出來；而在宅配困難的情況下，光靠大台北地區自取，就能衝出一定數量。除了熟客群支持，應也能觸及平常接觸不到的客人。

更有意思的是，田原主廚的把煮麵這件事，說明得叨絮囉唆，就是一個控制狂把煮培根起司蛋麵的一切變因都想清楚了，從器具、事前準備到實際製作，萬無一失地交代囑咐。他希望我們在家也能像在logy一樣，品嘗到完美。即便只是平凡到不行的carbonara。

為了示範精準的煮麵水鹹度，又怕有些人家裡無法度量幾公升的水、幾公克的鹽，他附了一小瓶「1%濃度鹽水」。我量了2公升的水、20公克的鹽，再和這瓶1%鹽水比較，真的，一樣。至此我才記好煮麵水該多鹹，在心裡感嘆「學習了」。

然後就該一帆風順了是吧？煮麵水完成，麵投入完成，醬汁回溫完成，計時一分不漏，濾水、拌麵，voila！

可是，拍照的時候我覺得怪怪的，這麵長得不太對勁。

吃完了才發現，還有一包帕瑪森起司粉與黑胡椒，我忘了加。

這才是藏在細節裡的魔鬼，哈哈哈哈。

💡評測心得：
logy的培根起司蛋麵，快速方便，味道精準，一包四份，滿適合作為儲糧。只是供貨不易，也會不定期更換產品，據說下一份是甜點呢。

#FoodGoBox #搞剛的餐廳主菜

FoodGo Box 食譜食材箱 是食材顧問商「FoodSeason 食時可樂」推出的meal kit，去年問世，今年改版，除了「經典威靈頓牛排」，還請「香色」餐廳主廚Steve研發「香色那可那可雞」。

二箱食材送到我家，打開一瞧，連上食譜一看，我眉頭一皺。好難，這二道菜是我目前為止做過的meal kit中最難的，又要包酥皮，又要綁雞捲，大量的手作讓我憂心。

沒想到，這二道菜我做得很順，成果也很美味。

手可以突然變巧的嗎？

或許是手氣較好。我順利地煎香菲力牛排、塗上黃芥末，完整包覆進蘑菇泥、生火腿與酥皮中，還用叉子畫上了菱格紋，烤的溫度與時間也剛好，漂亮的上色，五分熟的肉質。我做出了威靈頓牛排。

香色的「那可那可雞」更讓我滿意。其實是鹽焗雞，用大量的鹽與蛋白蓋成鹽的厚牆，把包進肉泥慕斯、裹上無花果葉的煙燻雞腿捲放進去烤。無花果葉的香氣非常棒，有如乾爽的森林，也如淡雅的稻草，芬芳滿室滿屋，令人愉悅。鹽焗後的雞捲也很美味，鮮嫩多汁，事先煙燻過的香氣，以及肉泥慕斯的濃郁，非常和諧。這完全是一道餐廳等級的主菜。

💡評測心得：
FoodGo Box採取單道菜的作法，一道菜單價落在新台幣680元至980元之間，確實是餐廳主菜的價格。較耗時，帶有儀式感，這樣的meal kit適合慶祝的場合，或者閒暇時吃一頓大餐，若之後有宴客需求也可考慮。

📜 [專欄新文章] Uniswap v3 Features Explained in Depth

✍️ 田少谷 Shao

📥 歡迎投稿： https://medium.com/taipei-ethereum-meetup #徵技術分享文 #使用心得 #教學文 #medium

Once again the game-changing DEX 🦄 👑

Image source: https://uniswap.org/blog/uniswap-v3/

Outline

0. Intro1. Uniswap & AMM recap2. Ticks 3. Concentrated liquidity4. Range orders: reversible limit orders5. Impacts of v36. Conclusion

0. Intro

The announcement of Uniswap v3 is no doubt one of the most exciting news in the DeFi place recently 🔥🔥🔥

While most have talked about the impact v3 can potentially bring on the market, seldom explain the delicate implementation techniques to realize all those amazing features, such as concentrated liquidity, limit-order-like range orders, etc.

Since I’ve covered Uniswap v1 & v2 (if you happen to know Mandarin, here are v1 & v2), there’s no reason for me to not cover v3 as well ✅

Thus, this article aims to guide readers through Uniswap v3, based on their official whitepaper and examples made on the announcement page. However, one needs not to be an engineer, as not many codes are involved, nor a math major, as the math involved is definitely taught in your high school, to fully understand the following content 😊😊😊

If you really make it through but still don’t get shxt, feedbacks are welcomed! 🙏

There should be another article focusing on the codebase, so stay tuned and let’s get started with some background noise!

1. Uniswap & AMM recap

Before diving in, we have to first recap the uniqueness of Uniswap and compare it to traditional order book exchanges.

Uniswap v1 & v2 are a kind of AMMs (automated market marker) that follow the constant product equation x * y = k, with x & y stand for the amount of two tokens X and Y in a pool and k as a constant.

Comparing to order book exchanges, AMMs, such as the previous versions of Uniswap, offer quite a distinct user experience:

AMMs have pricing functions that offer the price for the two tokens, which make their users always price takers, while users of order book exchanges can be both makers or takers.

Uniswap as well as most AMMs have infinite liquidity¹, while order book exchanges don’t. The liquidity of Uniswap v1 & v2 is provided throughout the price range [0,∞]².

Uniswap as well as most AMMs have price slippage³ and it’s due to the pricing function, while there isn’t always price slippage on order book exchanges as long as an order is fulfilled within one tick.

In an order book, each price (whether in green or red) is a tick. Image source: https://ftx.com/trade/BTC-PERP

¹ though the price gets worse over time; AMM of constant sum such as mStable does not have infinite liquidity

² the range is in fact [-∞,∞], while a price in most cases won’t be negative

³ AMM of constant sum does not have price slippage

2. Tick

The whole innovation of Uniswap v3 starts from ticks.

For those unfamiliar with what is a tick:

Source: https://www.investopedia.com/terms/t/tick.asp

By slicing the price range [0,∞] into numerous granular ticks, trading on v3 is highly similar to trading on order book exchanges, with only three differences:

The price range of each tick is predefined by the system instead of being proposed by users.

Trades that happen within a tick still follows the pricing function of the AMM, while the equation has to be updated once the price crosses the tick.

Orders can be executed with any price within the price range, instead of being fulfilled at the same one price on order book exchanges.

With the tick design, Uniswap v3 possesses most of the merits of both AMM and an order book exchange! 💯💯💯

So, how is the price range of a tick decided?

This question is actually somewhat related to the tick explanation above: the minimum tick size for stocks trading above 1$ is one cent.

The underlying meaning of a tick size traditionally being one cent is that one cent (1% of 1$) is the basis point of price changes between ticks, ex: 1.02 — 1.01 = 0.1.

Uniswap v3 employs a similar idea: compared to the previous/next price, the price change should always be 0.01% = 1 basis point.

However, notice the difference is that in the traditional basis point, the price change is defined with subtraction, while here in Uniswap it’s division.

This is how price ranges of ticks are decided⁴:

Image source: https://uniswap.org/whitepaper-v3.pdf

With the above equation, the tick/price range can be recorded in the index form [i, i+1], instead of some crazy numbers such as 1.0001¹⁰⁰ = 1.0100496621.

As each price is the multiplication of 1.0001 of the previous price, the price change is always 1.0001 — 1 = 0.0001 = 0.01%.

For example, when i=1, p(1) = 1.0001; when i=2, p(2) = 1.00020001.

p(2) / p(1) = 1.00020001 / 1.0001 = 1.0001

See the connection between the traditional basis point 1 cent (=1% of 1$) and Uniswap v3’s basis point 0.01%?

Image source: https://tenor.com/view/coin-master-cool-gif-19748052

But sir, are prices really granular enough? There are many shitcoins with prices less than 0.000001$. Will such prices be covered as well?

Price range: max & min

To know if an extremely small price is covered or not, we have to figure out the max & min price range of v3 by looking into the spec: there is a int24 tick state variable in UniswapV3Pool.sol.

Image source: https://uniswap.org/whitepaper-v3.pdf

The reason for a signed integer int instead of an uint is that negative power represents prices less than 1 but greater than 0.

24 bits can cover the range between 1.0001 ^ (2²³ — 1) and 1.0001 ^ -(2)²³. Even Google cannot calculate such numbers, so allow me to offer smaller values to have a rough idea of the whole price range:

1.0001 ^ (2¹⁸) = 242,214,459,604.341

1.0001 ^ -(2¹⁷) = 0.000002031888943

I think it’s safe to say that with a int24 the range can cover > 99.99% of the prices of all assets in the universe 👌

⁴ For implementation concern, however, a square root is added to both sides of the equation.

How about finding out which tick does a price belong to?

Tick index from price

The answer to this question is rather easy, as we know that p(i) = 1.0001^i, simply takes a log with base 1.0001 on both sides of the equation⁴:

Image source: https://www.codecogs.com/latex/eqneditor.php

Let’s try this out, say we wanna find out the tick index of 1000000.

Image source: https://ncalculators.com/number-conversion/log-logarithm-calculator.htm

Now, 1.0001¹³⁸¹⁶² = 999,998.678087146. Voila!

⁵ This formula is also slightly modified to fit the real implementation usage.

3. Concentrated liquidity

Now that we know how ticks and price ranges are decided, let’s talk about how orders are executed in a tick, what is concentrated liquidity and how it enables v3 to compete with stablecoin-specialized DEXs (decentralized exchange), such as Curve, by improving the capital efficiency.

Concentrated liquidity means LPs (liquidity providers) can provide liquidity to any price range/tick at their wish, which causes the liquidity to be imbalanced in ticks.

As each tick has a different liquidity depth, the corresponding pricing function x * y = k also won’t be the same!

Each tick has its own liquidity depth. Image source: https://uniswap.org/blog/uniswap-v3/

Mmm… examples are always helpful for abstract descriptions 😂

Say the original pricing function is 100(x) * 1000(y) = 100000(k), with the price of X token 1000 / 100 = 10 and we’re now in the price range [9.08, 11.08].

If the liquidity of the price range [11.08, 13.08] is the same as [9.08, 11.08], we don’t have to modify the pricing function if the price goes from 10 to 11.08, which is the boundary between two ticks.

The price of X is 1052.63 / 95 = 11.08 when the equation is 1052.63 * 95 = 100000.

However, if the liquidity of the price range [11.08, 13.08] is two times that of the current range [9.08, 11.08], balances of x and y should be doubled, which makes the equation become 2105.26 * 220 = 400000, which is (1052.63 * 2) * (110 * 2) = (100000 * 2 * 2).

We can observe the following two points from the above example:

Trades always follow the pricing function x * y = k, while once the price crosses the current price range/tick, the liquidity/equation has to be updated.

√(x * y) = √k = L is how we represent the liquidity, as I say the liquidity of x * y = 400000 is two times the liquidity of x * y = 100000, as √(400000 / 100000) = 2.

What’s more, compared to liquidity on v1 & v2 is always spread across [0,∞], liquidity on v3 can be concentrated within certain price ranges and thus results in higher capital efficiency from traders’ swapping fees!

Let’s say if I provide liquidity in the range [1200, 2800], the capital efficiency will then be 4.24x higher than v2 with the range [0,∞] 😮😮😮 There’s a capital efficiency comparison calculator, make sure to try it out!

Image source: https://uniswap.org/blog/uniswap-v3/

It’s worth noticing that the concept of concentrated liquidity was proposed and already implemented by Kyper, prior to Uniswap, which is called Automated Price Reserve in their case.⁵

⁶ Thanks to Yenwen Feng for the information.

4. Range orders: reversible limit orders

As explained in the above section, LPs of v3 can provide liquidity to any price range/tick at their wish. Depending on the current price and the targeted price range, there are three scenarios:

current price < the targeted price range

current price > the targeted price range

current price belongs to the targeted price range

The first two scenarios are called range orders. They have unique characteristics and are essentially fee-earning reversible limit orders, which will be explained later.

The last case is the exact same liquidity providing mechanism as the previous versions: LPs provide liquidity in both tokens of the same value (= amount * price).

There’s also an identical product to the case: grid trading, a very powerful investment tool for a time of consolidation. Dunno what’s grid trading? Check out Binance’s explanation on this, as this topic won’t be covered!

In fact, LPs of Uniswap v1 & v2 are grid trading with a range of [0,∞] and the entry price as the baseline.

Range orders

To understand range orders, we’d have to first revisit how price is discovered on Uniswap with the equation x * y = k, for x & y stand for the amount of two tokens X and Y and k as a constant.

The price of X compared to Y is y / x, which means how many Y one can get for 1 unit of X, and vice versa the price of Y compared to X is x / y.

For the price of X to go up, y has to increase and x decrease.

With this pricing mechanism in mind, it’s example time!

Say an LP plans to place liquidity in the price range [15.625, 17.313], higher than the current price of X 10, when 100(x) * 1000(y) = 100000(k).

The price of X is 1250 / 80 = 15.625 when the equation is 80 * 1250 = 100000.

The price of X is 1315.789 / 76 = 17.313 when the equation is 76 * 1315.789 = 100000.

If now the price of X reaches 15.625, the only way for the price of X to go even higher is to further increase y and decrease x, which means exchanging a certain amount of X for Y.

Thus, to provide liquidity in the range [15.625, 17.313], an LP needs only to prepare 80 — 76 = 4 of X. If the price exceeds 17.313, all 4 X of the LP is swapped into 1315.789 — 1250 = 65.798 Y, and then the LP has nothing more to do with the pool, as his/her liquidity is drained.

What if the price stays in the range? It’s exactly what LPs would love to see, as they can earn swapping fees for all transactions in the range! Also, the balance of X will swing between [76, 80] and the balance of Y between [1250, 1315.789].

This might not be obvious, but the example above shows an interesting insight: if the liquidity of one token is provided, only when the token becomes more valuable will it be exchanged for the less valuable one.

…wut? 🤔

Remember that if 4 X is provided within [15.625, 17.313], only when the price of X goes up from 15.625 to 17.313 is 4 X gradually swapped into Y, the less valuable one!

What if the price of X drops back immediately after reaching 17.313? As X becomes less valuable, others are going to exchange Y for X.

The below image illustrates the scenario of DAI/USDC pair with a price range of [1.001, 1.002] well: the pool is always composed entirely of one token on both sides of the tick, while in the middle 1.001499⁶ is of both tokens.

Image source: https://uniswap.org/blog/uniswap-v3/

Similarly, to provide liquidity in a price range < current price, an LP has to prepare a certain amount of Y for others to exchange Y for X within the range.

To wrap up such an interesting feature, we know that:

Only one token is required for range orders.

Only when the current price is within the range of the range order can LP earn trading fees. This is the main reason why most people believe LPs of v3 have to monitor the price more actively to maximize their income, which also means that LPs of v3 have become arbitrageurs 🤯

I will be discussing more the impacts of v3 in 5. Impacts of v3.

⁷ 1.001499988 = √(1.0001 * 1.0002) is the geometric mean of 1.0001 and 1.0002. The implication is that the geometric mean of two prices is the average execution price within the range of the two prices.

Reversible limit orders

As the example in the last section demonstrates, if there is 4 X in range [15.625, 17.313], the 4 X will be completely converted into 65.798 Y when the price goes over 17.313.

We all know that a price can stay in a wide range such as [10, 11] for quite some time, while it’s unlikely so in a narrow range such as [15.625, 15.626].

Thus, if an LP provides liquidity in [15.625, 15.626], we can expect that once the price of X goes over 15.625 and immediately also 15.626, and does not drop back, all X are then forever converted into Y.

The concept of having a targeted price and the order will be executed after the price is crossed is exactly the concept of limit orders! The only difference is that if the range of a range order is not narrow enough, it’s highly possible that the conversion of tokens will be reverted once the price falls back to the range.

As price ranges follow the equation p(i) = 1.0001 ^ i, the range can be quite narrow and a range order can thus effectively serve as a limit order:

When i = 27490, 1.0001²⁷⁴⁹⁰ = 15.6248.⁸

When i = 27491, 1.0001²⁷⁴⁹¹ = 15.6264.⁸

A range of 0.0016 is not THAT narrow but can certainly satisfy most limit order use cases!

⁸ As mentioned previously in note #4, there is a square root in the equation of the price and index, thus the numbers here are for explantion only.

5. Impacts of v3

Higher capital efficiency, LPs become arbitrageurs… as v3 has made tons of radical changes, I’d like to summarize my personal takes of the impacts of v3:

Higher capital efficiency makes one of the most frequently considered indices in DeFi: TVL, total value locked, becomes less meaningful, as 1$ on Uniswap v3 might have the same effect as 100$ or even 2000$ on v2.

The ease of spot exchanging between spot exchanges used to be a huge advantage of spot markets over derivative markets. As LPs will take up the role of arbitrageurs and arbitraging is more likely to happen on v3 itself other than between DEXs, this gap is narrowed … to what extent? No idea though.

LP strategies and the aggregation of NFT of Uniswap v3 liquidity token are becoming the blue ocean for new DeFi startups: see Visor and Lixir. In fact, this might be the turning point for both DeFi and NFT: the two main reasons of blockchain going mainstream now come to the alignment of interest: solving the $$ problem 😏😏😏

In the right venue, which means a place where transaction fees are low enough, such as Optimism, we might see Algo trading firms coming in to share the market of designing LP strategies on Uniswap v3, as I believe Algo trading is way stronger than on-chain strategies or DAO voting to add liquidity that sort of thing.

After reading this article by Parsec.finance: The Dex to Rule Them All, I cannot help but wonder: maybe there is going to be centralized crypto exchanges adopting v3’s approach. The reason is that since orders of LPs in the same tick are executed pro-rata, the endless front-running speeding-competition issue in the Algo trading world, to some degree, is… solved? 🤔

Anyway, personal opinions can be biased and seriously wrong 🙈 I’m merely throwing out a sprat to catch a whale. Having a different voice? Leave your comment down below!

6. Conclusion

That was kinda tough, isn’t it? Glad you make it through here 🥂🥂🥂

There are actually many more details and also a huge section of Oracle yet to be covered. However, since this article is more about features and targeting normal DeFi users, I’ll leave those to the next one; hope there is one 😅

If you have any doubt or find any mistake, please feel free to reach out to me and I’d try to reply AFAP!

Stay tuned and in the meantime let’s wait and see how Uniswap v3 is again pioneering the innovation of DeFi 🌟

Uniswap v3 Features Explained in Depth was originally published in Taipei Ethereum Meetup on Medium, where people are continuing the conversation by highlighting and responding to this story.

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