Loading Resources

Local and external resources made available in interactive code blocks

Normally webr and pyodide code blocks are executed in the reader’s web browser, and so resources local to your own machine are not available for use inside the WebAssembly environment. Instead, there is a Virtual Filesystem (VFS) made available that contains only the minimum required to run R or Python code.

Local resources

To make a file or directory in your local system available under WebAssembly, add the path to the resources key in your document’s YAML header. The quarto-live extension will automatically download named resources into the WebAssembly VFS as R or Python starts up. The resources will be made available in the current working directory (usually /home/web_user).

R

Source

resources.qmd

---
format: live-html
resources:
  - data
---

```{webr}
list.files("data")
mt <- read.csv("data/mtcars.csv")
mod <- glm(mpg ~ cyl, data = mt)
summary(mod)
```

Output

Python

Source

resources.qmd

---
format: live-html
resources:
  - data
---

```{pyodide}
from os import listdir
import pandas as pd
print(listdir("data"))
pd.read_csv('data/mtcars.csv')
```

Output

Loading only a subset

By default, any resource listed under resources will be added to the R and Python VFS. However, you might want to include many resources with your document, but only load a subset of them into the VFS. Use the resources key under webr and pyodide to indicate which resources will be loaded.

R

resources.qmd

---
format: live-html
resources:
  - "data"
webr:
  resources:
    - data/mtcars.csv
---

Python

resources.qmd

---
format: live-html
resources:
  - "data"
pyodide:
  resources:
    - data/mtcars.csv
---

Remote resources

Remote resource URLs can be included in the resources key, under webr and pyodide, in your document’s YAML header. The listed resources will be downloaded as the page loads and made available in the R or Python VFS.

Note

Resources loaded by URL from a remote server must be served with Cross-Origin Resource Sharing (CORS) headers to allow access.

R

Source

url.qmd

---
format: live-html
webr:
  resources:
    - https://raw.githubusercontent.com/mwaskom/seaborn-data/master/flights.csv
---

```{webr}
flights <- read.csv("flights.csv")
with(flights, plot(year, passengers))
```

Output

Python

Source

url.qmd

---
format: live-html
pyodide:
  resources:
    - https://raw.githubusercontent.com/mwaskom/seaborn-data/master/flights.csv
---

```{pyodide}
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

flights = pd.read_csv('data/flights.csv')
sns.relplot(
  data = flights,
  x = "year",
  y = "passengers"
)
plt.show()
```

Output