MDAO 301 Session 2
Session 2 features finding user activities or protocol usage. The example that we'll be using is Curve Fi dex
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Using decoded logs
Using token transfers for liquidity events
Dashboard Assignment
Using the ez dex swaps table
Use decoded logs to find all event names that are related to liquidity events
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1. First, find a pool address - use docs/etherscan/protocol website to find one
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2. Search for sample transactions on Etherscan
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3. Plug address as contract address to find possibly event names
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4. Then filter for events you want and use the decoded_log column to get the information you need (fees, liquidity provider, amount, etc)
- Create charts to show observations about liquidity for the protocol. Is the trend a short term trend? What does it look like over the long term? Is this a cause for concern?
Some thinking points for your own deep dive:
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- What about other similar protocols? Do they see an incline/decline over the same period too?
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- is the majority of the liquidity added by only a handful of addresses?
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- you don't have to answer all these questions, but these are some of the deeper dives you can get into
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1. Go beyond "active" users - too common to see dashboards counting distinct address interacting with a protocol each day
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2. Create histograms like this so you can ask deeper questions - why do most people only swap once? What is the most used swap route in this category?
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1. Use a normalized area graph to show marketshare.
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2. Play around with ordering your values in descending/ascending order to show a "nicer" graph
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1. Create a dashboard visualizing user activities of a DEX of your choice. For ease of data, choose the list of dex from the dex swaps table. Your dashboard should contain:
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a. A raw table showcasing transactions of adding or removing liquidity for a pool in the dex using the decoded_logs table
b. Liquidity events - this could be cumulative liquidity added or removed or could be about the users who provided the liquidity
c. Swaps - show interesting stats about users who swap on the dex - this could be user distribution histograms, "high activity users", etc
d. Marketshare - show marketshare using a normalized area graph - this could be a comparison of swaps of dexes, or number of transactions / liquidity actions
2. Share any insights to observations around the liquidity events and swaps
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3. Use appropriate graphs to show the data
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4. Dashboard is due next week EOD, submit your dashboard here