Carl Cervone

Epic: Identify developer movement between web2, crypto and AI

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The goal is to create a sankey chart that allows a user to filter on an ecosystem (from the Open Dev Data taxonomy) and identify developer movement to/from different ecosystems.

Diff OSO / gharchive commits vs OpenDevData

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Here's a starter notebook: [https://www.oso.xyz/oso/OSO-vs-ODD](https://www.oso.xyz/oso/OSO-vs-ODD)

Epic: Landing page copy and embeddable assets

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To update the landing page, we need the following: * Refreshed copy * A high quality generic "builder dashboard" view that can be embedded for the hero section * Other...

Reworked copy for main page and each solutions, plus preview images

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- [ ] Solutions on landing page and navbar - [ ] Ecosystem Growth - [ ] Venture Capital - [ ] Supply Chain - [ ] Reputation Networks -...

Run a clustering algorithm to auto-label projects and facilitate DDP data cleaning

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Test out a few options for categorizing repos

Notebook URLs should be case-insensitive

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This works:[https://www.oso.xyz/optimism/Retro-Funding-Devtooling-Results](https://www.oso.xyz/optimism/Retro-Funding-Devtooling-Results) This 404s: [https://www.oso.xyz/optimism/Retro-Funding-Devtooling-results](https://www.oso.xyz/optimism/Retro-Funding-Devtooling-Results)

Epic: Refactor `COMMITS` to `PUSH` events

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Given the recent GItHub API changes, we need to make a series of changes to replace `COMMIT` logic with `PUSH` event logic. Alternatively, we could keep commits but change the...

Update models / notebooks downstream from timeseries metrics to use `push` events

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Unfortunately, this metric shows up a lot … we'd need to look for it across a variety of surfaces, from Retro Funding algos to production notebooks

Use `push` event logic wherever we used to have `commit` logic

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This includes several core intermediate models like `int_first_last_commit_to_github_repository` as well as definitions for active developers, contributors, etc in the metrics factory.

Create new timeseries metrics for `push_events`

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We'd want to create the usual timeseries metrics for these events, like we have for other GitHub events like stars and commits