📜 [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.
👏 歡迎轉載分享鼓掌
同時也有3部Youtube影片,追蹤數超過93萬的網紅Ytower Cooking channel,也在其Youtube影片中提到,韓國mami cook不沾全套鍋組→ https://goo.gl/2odLVw 1.三杯雞 材料 雞肉1500公克 薑片100公克 蒜仁80公克 辣椒3支 九層塔葉30公克 調味料 胡麻油100公克 醬油膏100公克 米酒100公克 糖2大匙 作法 1.熱鍋,加入麻油、薑片以小火煸炒至微微焦香...
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อันยองงง วันนี้วันอาทิตย์วันดี ไนซ์ว่างๆก็เลยมาอัพเดทการแต่งหน้าซักหน่อย เป็นลุคี่แต่งตามกันได้ง่ายๆ ทั้งผู้ชาย ผู้หญิง เน้นงานผิวง่ายๆใสๆ เครื่องสำอางก็หาซื้อได้ง่ายๆ แต่จริงๆคลิปสั้นๆ ไนซ์จะเอาไปอัพที่ช่องTiktok ก็สามารถไปตามเพิ่มกันได้น้าา
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sprat 在 巴黎玩家謝忠道 Facebook 的最佳貼文
法式抗疫(二十一)
巴黎又開始春光明媚, 鳥語花香的氣候了!
早上起床, 陽光燦爛, 我們一家四口的精神都很好: 泡好咖啡, 和阿杯一起到陽台上增強維他命D, 展現好公民的團結, 強力抗疫.
咖啡慢慢喝, 阿蘭阿花慢慢噴, 指甲慢慢剪, 牙齒一顆顆刷, 不必記得今天是禮拜幾, 現在幾點.
沒有甚麼天塌下來的事需要急著處理.
人間祥和, 歲月靜好, 如果不打開電視的話.
可是今天打開電視, 頭條竟然不是病毒疫情, 是南部小鎮Romans-Sur-Isère有人持刀攻擊, 造成2死7傷! 目前還不知道是恐攻, 還是哪個腦袋不正常的瘋子…
一刺激腦子醒了, 就想起昨天晚上法國疫情總指揮所羅門公布的災情: 增加588死亡, 總數達6507. 從疫情爆發以來, 老人院裡已經掛了1614人了, 成了另一個重災區. 但是所羅門指揮官沒有說明這1614人裡面有多少是死於武肺的.
大巴黎區已經迎頭趕上大東區Grand-Est, 成為法國災情最嚴重的地區. 現在連巴黎市南邊的中央市場Rungis都騰出來當殯儀館, 停屍場. 受到政府招喚的退休醫護人員, 醫療系學生… 開始湧向負荷最重的地方支援.
除了恐攻以外, 沒被法國人這麼無私的團結感動過.
當然, 自私的人哪裏都有. 偏偏碰上復活節大假.
內政部長出來大喊: 給我乖乖待在家裡, 都不准出去度假! 派出16萬警察在路口, 車站, 觀光景點臨檢.
法國人最愛的日常活動: 示威, 遊行, 罷工, 度假… 一一被禁止. 悶爆了.
媒體還在爭吵到底要不要用奎寧類藥品, 該不該戴口罩. 看得讓人直翻白眼.
法國生活急凍, 郵差一周只送三天, 所有郵務都延遲. 難怪, 3月24日訂的咖啡豆, 從里昂出發到現在還在路上. 用走的也該到了吧? (白眼)
非常無奈.
可是日子還是要過啊. 想想喫甚麼比較實際.
前天買的不要想歪大香腸還有一條. 省著喫, 半條切段兩面煎香. 馬鈴薯煮熟切塊, 和香腸一起放鍋裡. 冰箱最後兩顆蛋, 打打倒進去.
這是懶人版的煎蛋. 不敢稱是西班牙的tortilla, 反正就是廚餘料理之一. 也是不難喫.
加碼來個改版魚罐頭沙拉. 今天改用沙丁魚的表弟sprat. 體型跟沙丁魚差不多, 肉質更軟嫩, 通常做成罐頭, 而且煙燻過. 鮮魚攤上也常見燻乾的, 便宜好喫.
抗疫時期鮮魚少見, 拿這種抵數也是很可以了: 小蘿蔓沙拉葉洗洗剝細, 醃黃瓜切切, 半乾番茄不用切直接放進來. 橄欖油巴薩米克酒醋醬.
慶祝週六好天氣, 昨天的美麗草莓也加來: 草莓去蒂, 切半, 灑糖醃漬. 幾小時後, 和一大碗白奶酪fromage blanc一起喫. 想到還有可人的龍眼蜜, 馬上升級成頂級龍眼蜜草莓白奶酪!
美麗的周六中午一個人午餐也是可以喫得心情很美麗.
剛才沒蛋了, 吃完來去超市買練習專業臉友們提供的糖心/水波蛋秘笈.
恐龍手套戴上, 蒙面俠口罩戴上, 購物袋信用卡. 記得走逃生梯下去, 萬一和大樓鄰居共擠電梯, 造成死傷.
樓梯走到一半, 聽到樓下有人聲! 敢情有人想法跟我一樣, 不搭電梯. 我正要返身上樓時, 樓上也出現人聲…
慘了, 我被卡在五樓逃生梯裡進退不得.
沒關係, 路不轉人轉. 迅速離開逃生梯, 遁入五樓樓層搭電梯. 正在等電梯時, 有胖太太拎著購物袋出來看到我: Bonjour… ㄟ, 你不是這一層的住戶吧?
呃… 這怎麼解釋啊, 我崩潰了…
不想跟胖太太擠電梯啊!
sprat 在 Ytower Cooking channel Youtube 的最讚貼文
韓國mami cook不沾全套鍋組→ https://goo.gl/2odLVw
1.三杯雞
材料
雞肉1500公克
薑片100公克
蒜仁80公克
辣椒3支
九層塔葉30公克
調味料
胡麻油100公克
醬油膏100公克
米酒100公克
糖2大匙
作法
1.熱鍋,加入麻油、薑片以小火煸炒至微微焦香。
2.放入蒜仁、辣椒炒至金黃。
3.放入雞肉炒至變色略變色。
4.加入油膏、米酒、糖炒勻。
5.蓋上鍋蓋燜煮約15分鐘。
6.加入九層塔葉炒勻即可。
2.宮保雞丁
材料:
雞腿丁 2片
乾辣椒 15公克
蒜末 10公克
蔥段 20公克
花生 100公克
調味料:
醬油 1大匙
白醋 2茶匙
糖 2茶匙
米酒 1大匙
太白粉 1茶匙
水 2茶匙
作法:
1.所有調味料拌勻成醬汁。
2.熱鍋,放入雞腿丁,將雞腿炒至焦香且煸出油脂。
3.接著放入蒜末、乾辣椒、蔥段爆香,淋上作法1的醬汁拌炒均勻,最後撒上花生即可。
3.左宗棠雞
材料:
雞腿排 800公克
辣椒 6根
醃料:
醬油 2大匙
太白粉 4大匙
雞蛋 1顆
米酒 1大匙
油 2大匙
醬汁:
醬油 2大匙
蕃茄醬 2大匙
白醋 2大匙
米酒 2大匙
蒜末 3大匙
太白粉 1大匙
糖 2大匙
水 1大匙
作法:
1.雞腿排用刀稍微在表面切紋路之後切成一口大小。
2.將雞肉塊與醃料抓勻,最後再加入油拌勻防止沾黏。
3.醬汁材料拌勻備用。
4.鍋中倒入適量油開大火加熱至180度,將肉倒入並不時攪拌將肉拌開,炸至雞肉表面金黃酥脆即可撈起。
5.原鍋煸香辣椒至微焦香後加入雞肉與醬汁扮炒翻勻即可。
4.麻油雞飯
材料:
米 4杯
雞肉塊 700公克
泡發香菇 150公克(約10朵)
薑絲 50公克
枸杞 20公克
水 6杯
麻油 3大匙
米酒 50cc
鹽 1茶匙
作法:
1.米洗淨後與水泡約半小時。
2.麻油倒入砂鍋內加熱後與薑絲煸香,再加入雞肉炒至變白。
3.再加入香菇炒香,加入米酒煮滾後舀起備用。
4.鍋內倒入米與水,加入枸杞、鹽煮滾後將其餘的料鋪上,以小火續煮12分鐘。
TIPS:料先舀起再鋪上,讓米泡到水才易熟
5.煮滾後加蓋燜10分鐘即可。
5.花雕雞
材料
土雞腿 1800公克
薑片 30公克
蒜片 30公克
蒜苗 100公克
宮保(乾辣椒) 5公克
花椒 5公克
芹菜 100公克
調味料
蠔油 2大匙
辣豆瓣醬 4大匙
花雕酒 100CC
水 50CC
作法
1.土雞腿洗淨剁小塊;蒜苗切片;芹菜切小段,備用。
2.熱鍋,倒入適量的油,放入蒜片、薑片爆香,再放入宮保(乾辣椒)、花椒炒香後,加入辣豆瓣醬。
3.放入雞肉拌炒,炒至雞肉乾香、表面呈微金黃色。
4.加入蠔油、花雕酒、水炒勻,煮至湯汁略收。
5.加入蒜苗片、芹菜段炒勻即可。
6.甕仔雞
材料
A
全雞1000公克 \ chicken 1000g
B
鹽1/2茶匙 \ salt 1/2tsp.
白胡椒粉1/4茶匙 \ white pepper powder 1/4tsp.
C
醬油1大匙 \ soy sauce 1tbsp.
D
蒜頭50公克 \ garlic 50g
洋蔥絲50公克 \ onion 50g
薑片10公克 \ ginger 10g
芹菜20公克 \ chinese celery 20g
米酒1大匙 \ cooking rice wine 1tbsp.
作法
1.雞身上撒上材料B塗抹均勻。
2.均勻抹上醬油塗勻。
3.雞腹塞入材料D。
4.將雞放在氣炸鍋的平煎盤上,表面均勻塗上油。
5.放入氣炸鍋中,設定180℃烤約18分鐘即可。
7.乾煎雞腿
材料:
醃製雞腿排 2片
高麗菜絲 適量
作法:
1.冷鍋將雞腿排朝雞皮面下鍋煎5分鐘至出油。
2.等底部邊緣變白後翻面再煎5分鐘。
3.呈盤後底下鋪高麗菜絲再放上雞排即可。
醃漬雞腿排
材料:
鹽 適量
黑胡椒 適量
米酒 1大匙
作法:
1.雞腿將厚薄片開,橫切斷筋
2.在雞腿排表面撒上鹽、黑胡椒與米酒醃製。
8.紹興醉雞
材料
A
帶骨雞腿3支 \ chicken thigh 3
紹興酒500ml \ Shaoxing wine 500ml
雞湯(煮雞產生)500ml \ chicken stock 500ml
B
薑片20公克 \ ginger 20g
蔥段20公克 \ scallion 20g
米酒2大匙 \ cooking rice wine 2tbsp.
C
當歸1片 \ dong quai 1
枸杞10公克 \ goji berry 10g
薑片15公克 \ ginger 15g
鹽1茶匙 \ salt 1tsp.
糖1茶匙 \ sugar 1tsp.
作法
1.煮一鍋水至滾,放入材料B,再放入雞腿。
2.待水續滾沸,轉小火煮5分鐘,加蓋關火浸泡15分鐘。
3.開蓋在雞腿最厚處用筷子戳一下,如果沒有流出血水就是熟透了。
4.雞腿冷卻後放入保鮮盒中,加入材料C與煮雞肉的雞湯,冷藏一晚即可。
9.香菇雞湯
材料:
A
雞肉 1200公克 chicken 1200g
B
乾香菇 30公克 dried shiitake mushroom 30g
薑片 30公克ginger slice 30g
紅棗 8顆 red date 8
米酒 2大匙 cooking rice wine 2tbsp
作法:
1.取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2.食物鍋中放入雞肉、所有材料B。
3.水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4.將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
10.鳳梨苦瓜雞湯
材料:
A
雞肉 800公克 chicken 800g
B
鳳梨黃豆醬 200公克 fermented pineapple and soy bean sauce 200g
蒜頭 50公克 garlic 50g
乾丁香魚 10公克 dried slender sprat 10g
苦瓜 500公克 bitter gourd 500g
米酒 2大匙 cooking rice wine 2tbsp
作法:
1.取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2.食物鍋中放入雞肉、所有材料B。
3.水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4.將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
-
楊桃美食網
http://www.ytower.com.tw
天天買菜 天菜網
http://www.skycook.com.tw
Youtube
https://www.youtube.com/user/ytower01
Facebook
https://www.facebook.com/ytower01
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sprat 在 Ytower Cooking channel Youtube 的最讚貼文
飛利浦 原汁萃取汽鍋醇湯煲 獨家優惠2990元
下殺3折 https://goo.gl/WzsCqg
1. 鳳梨苦瓜雞湯
材料:
A
雞肉 800公克 chicken 800g
B
鳳梨黃豆醬 200公克 fermented pineapple and soy bean sauce 200g
蒜頭 50公克 garlic 50g
乾丁香魚 10公克 dried slender sprat 10g
苦瓜 500公克 bitter gourd 500g
米酒 2大匙 cooking rice wine 2tbsp
作法:
1. 取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2. 食物鍋中放入雞肉、所有材料B。
3. 水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4. 將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
2. 香菇雞湯
材料:
A
雞肉 1200公克 chicken 1200g
B
乾香菇 30公克 dried shiitake mushroom 30g
薑片 30公克ginger slice 30g
紅棗 8顆 red date 8
米酒 2大匙 cooking rice wine 2tbsp
作法:
1. 取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2. 食物鍋中放入雞肉、所有材料B。
3. 水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4. 將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
3. 菜脯雞湯
材料:
A
雞肉 1200公克 chicken 1200g
B
菜脯 120公克 preserved radish 120g
老菜脯 30公克fermented radish 30g
蒜頭 60公克 garlic 60g
米酒 2大匙 cooking rice wine 2tbsp
作法:
1. 取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2. 食物鍋中放入雞肉、所有材料B。
3. 水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4. 將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
4. 剝皮辣椒雞湯
材料:
A
雞肉 1200公克 chicken 1200g
B
剝皮辣椒+汁 250公克 skinned pickled green chili with sauce 250g
蒜頭 50公克 garlic 50g
薑片 30公克 ginger slices 30g
米酒 2大匙 cooking rice wine 2tbsp
作法:
1. 取另一鍋煮水,將雞肉稍微汆燙後撈起泡冷水沖洗。
2. 食物鍋中放入雞肉、所有材料B。
3. 水鍋中倒入水至1.9L的位置,再將水鍋放在機座上。
4. 將食物鍋放在水鍋上,蓋上鍋蓋,設定2小時(順時針旋轉)即可。
-
楊桃美食網
http://www.ytower.com.tw
天天買菜 天菜網
http://www.skycook.com.tw
Youtube
https://www.youtube.com/user/ytower01
Facebook
https://www.facebook.com/ytower01
![post-title](https://i.ytimg.com/vi/gmCTqn5-UgQ/hqdefault.jpg?sqp=-oaymwEZCNACELwBSFXyq4qpAwsIARUAAIhCGAFwAQ==&rs=AOn4CLCqBnSTt-Jh5wOIrTlujf4aEP47UA)
sprat 在 WenWei彣蔚 Youtube 的精選貼文
Instagram. : @wen_weiyy / @wenwei21
Shop on instagram : @sparkletoolscosmetics
Musically : @wen_weiyy
Product ive used in the video
Benefit - liquid foundation
Mac - concealer
Real teqniques - beauty sponge
RCMA - no color powder
Benefit- bronzer
Tanya burr - perfect brows
Morphe - 350m palette
Colourpop - nillionaire super shock shadow
Violet voss - pro palette
Maybeline -eyeliner
Nyx - eyeliner
Forever 21 - curler
Forever 21- eyelashes
Too faced - better than sex mascara
Revolution - blush palette
Anastasia glow kit - sun dipped
Colourpop - ultra matte lip "beeper"
Nyx - setting sprat (matte)
Bastie - dry shampoo
** u can get most of the products from my instagram shop : @sparkletoolscosmetics at a low price :) ??? to get a discount , just quote "wenwei" . Thanks for watching y'all ??
Song :
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sprat 在 How To Prepare Jamaican Fried Sprat Fish - YouTube 的推薦與評價
![影片讀取中](/images/youtube.png)
How To Prepare Jamaican Fried Sprat Fish. 6,497 views6.4K views. Mar 4, 2022. 375. Dislike. Share. Save. The Jamaican Cooking Journey. ... <看更多>
sprat 在 Sprat - 主頁 | Facebook 的推薦與評價
Sprat je bar sa akcentom na craft pivima, bleji i društvenim igrama. Nalazi se u Cetinjskoj ulici... Cetinjska 15, 塞尔维亚贝尔格莱德. ... <看更多>