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Merged
merged 12 commits into from
Apr 29, 2025
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2 changes: 1 addition & 1 deletion .github/workflows/blog.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -29,7 +29,7 @@ jobs:
run: |
Rscript ./dependencies.R
- name: Restore Blogdown Cache
uses: actions/cache@v4.2.2
uses: actions/cache@v4
with:
path: |
./blogdown
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2 changes: 1 addition & 1 deletion .github/workflows/ci.yaml
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@ jobs:
- uses: actions/setup-node@v4
with:
node-version: 18
- uses: actions/cache@v4.2.2
- uses: actions/cache@v4
with:
path: ~/.npm
key: ${{ runner.os }}-node3-${{ hashFiles('**/package-lock.json') }}
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2 changes: 1 addition & 1 deletion .github/workflows/release_main.yml
Original file line number Diff line number Diff line change
Expand Up @@ -47,7 +47,7 @@ jobs:
with:
node-version: 18
- name: Cache Node.js modules
uses: actions/cache@v4.2.2
uses: actions/cache@v4
with:
path: ~/.npm # npm cache files are stored in `~/.npm` on Linux/macOS
key: ${{ runner.OS }}-node2-${{ hashFiles('**/package-lock.json') }}
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8 changes: 4 additions & 4 deletions content/code/_index.md
Original file line number Diff line number Diff line change
Expand Up @@ -16,12 +16,12 @@ The core server code for the [Delphi Epidata API](https://cmu-delphi.github.io/d
### [Epidatr](https://cmu-delphi.github.io/epidatr/)

R client for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
It allows you to cache queries locally to speed up data access and seamlessly integrate pulling from our API into your pipelines.
Download data from our API as a usable tibble in R!

### [Epidatpy](https://github.com/cmu-delphi/epidatpy) (WIP)
### [Epidatpy](https://github.com/cmu-delphi/epidatpy)

A work-in-progress Python client for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
Not yet recommended for production, but we are happy to receive feedback!
Python client for the [Delphi Epidata API](https://cmu-delphi.github.io/delphi-epidata/).
Download data from our API as a usable Pandas dataframe in Python!

## Forecasting

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