# \[ANN\] USDAQuickStats.jl 1.0.0

**URL:** <https://discourse.julialang.org/t/ann-usdaquickstats-jl-1-0-0/136662>\
**Category:** Package Announcements\
**Created:** [April 10, 2026, 2:58am UTC](https://discourse.julialang.org/t/ann-usdaquickstats-jl-1-0-0/136662 "2026-04-10T02:58:58Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![alejandromerchan](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/alejandromerchan/32/10500_2.png) [@alejandromerchan](https://discourse.julialang.org/u/alejandromerchan)\
**Post date:** [April 10, 2026, 2:58am UTC](https://discourse.julialang.org/t/ann-usdaquickstats-jl-1-0-0/136662/1 "2026-04-10T02:58:58Z")

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# USDAQuickStats.jl 1.0.0

I’m happy to announce the release of [USDAQuickStats.jl](https://github.com/alejandromerchan/USDAQuickStats.jl) v1.0.0, the first stable version of the package.

## What the package does

[USDAQuickStats.jl](https://github.com/alejandromerchan/USDAQuickStats.jl) wraps the [USDA NASS Quick Stats API](https://quickstats.nass.usda.gov/api), giving Julia users easy programmatic access to one of the most comprehensive databases of US agricultural market data. The only core dependency is HTTP.jl, keeping things lightweight. A DataFrames extension is also available via `get_nass_df` for those who want results ready to analyze.

## Quick example

```julia
using USDAQuickStats

set_api_key("your-api-key")

# Check record count before querying
get_counts("source_desc=SURVEY", "commodity_desc=ORANGES", "state_alpha=CA", "year=2019")
# 957

# Fetch raw data
data = get_nass(
    "source_desc=SURVEY",
    "commodity_desc=ORANGES",
    "state_alpha=CA",
    "year=2019"
)

# Or get a DataFrame directly (requires DataFrames, JSON3, JSONTables, CSV)
using DataFrames, JSON3, JSONTables, CSV

df = get_nass_df(
    "source_desc=SURVEY",
    "commodity_desc=ORANGES",
    "state_alpha=CA",
    "year=2019"
)

```

## What’s new in 1.0.0

- ✅ Full test suite
- 📖 Proper documentation
- 🔒 Stable, committed public API
- 🧹 Modernized package structure

If you work with agricultural data in Julia, give it a try — and as always, PRs and feedback are welcome.