# Quickstart

This page gets you from installation to a computed index in a few commands. The command line is the fastest way to start. The commands below install the package, compute the index for `Tamagotchi` and `Furby` (written to `index.csv`), and launch the Shiny app.

``` bash
pip install nostalgia_index
nostalgia fetch Tamagotchi Furby --out index.csv
nostalgia run
```

From Python, the same steps take three calls. [fetch_views()](../reference/fetch_views.md#nostalgia_index.fetch_views) downloads daily pageviews for one article, [fetch_project_total()](../reference/fetch_project_total.md#nostalgia_index.fetch_project_total) downloads total English Wikipedia traffic to use as the denominator, and `NostalgiaIndex().compute()` combines them.

``` python
from nostalgia_index import fetch_views, fetch_project_total, NostalgiaIndex

views = fetch_views("Furby")
totals = fetch_project_total()
idx = NostalgiaIndex().compute(views, totals)
```


*\[Rich HTML output -- view on the documentation site\]*


The result in `idx` is a DataFrame with one row per article per day. The `nostalgia_index` column holds the scaled index, where 100 equals the article's level during its first 12 months. The first request for each article goes to the Wikimedia API; repeat requests read from a local cache on disk.