Example Usage

Bulk CSV Downloads is in early beta. We'd love your feedback — please reach out with any questions or issues.

All examples below use --profile gridstatus which assumes you have configured the named profile as described in Getting Started.

List available datasets

aws s3 ls s3://gs-catalog-csv/run=2026-02-17/ --profile gridstatus

PRE aeso_daily_average_pool_price/
PRE aeso_fuel_mix/
PRE aeso_interchange/
PRE aeso_load/
PRE aeso_load_forecast/
PRE caiso_as_prices/
PRE caiso_curtailment/
PRE caiso_fuel_mix/
PRE caiso_lmp_day_ahead_hourly/
PRE caiso_lmp_real_time_5_min/
...

Each PRE entry is a dataset folder. There may be hundreds of datasets depending on your export.

Explore available data range within a dataset

List the available years:

aws s3 ls s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/ --profile gridstatus

PRE year=2018/
PRE year=2019/
PRE year=2020/
PRE year=2021/
PRE year=2022/
PRE year=2023/
PRE year=2024/
PRE year=2025/
PRE year=2026/

List months within a year:

aws s3 ls s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/ --profile gridstatus

PRE month=01/
PRE month=02/
PRE month=03/
...
PRE month=12/

List individual files within a month:

aws s3 ls s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/month=01/ --profile gridstatus

2026-02-18 21:26:05       9064 2025-01-01.csv.gz
2026-02-18 21:26:08       9235 2025-01-02.csv.gz
2026-02-18 21:26:07       9171 2025-01-03.csv.gz
...
2026-02-18 21:26:33       9442 2025-01-31.csv.gz

Get total file count and size for an entire dataset with --recursive --summarize:

aws s3 ls s3://gs-catalog-csv/run=2026-02-17/pjm_lmp_real_time_5_min/ --recursive --summarize --profile gridstatus

...
2026-02-18 07:34:20  115232137 run=2026-02-17/pjm_lmp_real_time_5_min/year=2026/month=02/2026-02-17.csv.gz

Total Objects: 2880
   Total Size: 228560459449

In this case, pjm_lmp_real_time_5_min contains 2,880 files totaling ~213 GB.

Download data

Download a single file with aws s3 cp:

aws s3 cp s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/month=01/2025-01-01.csv.gz ./data/ --profile gridstatus

download: s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/month=01/2025-01-01.csv.gz to data/2025-01-01.csv.gz

Sync an entire dataset to a local folder:

aws s3 sync s3://gs-catalog-csv/run=2026-02-17/ercot_spp_day_ahead_hourly/ ./data/ercot_spp_day_ahead_hourly/ --profile gridstatus

download: s3://...ercot_spp_day_ahead_hourly/year=2019/month=01/2019-01-01.csv.gz to data/ercot_spp_day_ahead_hourly/year=2019/month=01/2019-01-01.csv.gz
download: s3://...ercot_spp_day_ahead_hourly/year=2019/month=01/2019-01-02.csv.gz to data/ercot_spp_day_ahead_hourly/year=2019/month=01/2019-01-02.csv.gz
...

Sync a single year:

aws s3 sync s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/ ./data/caiso_fuel_mix/year=2025/ --profile gridstatus

Sync a single month:

aws s3 sync s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/month=01/ ./data/caiso_fuel_mix/year=2025/month=01/ --profile gridstatus

Use --exclude and --include to filter specific files within a year (e.g. only June 2025):

aws s3 sync s3://gs-catalog-csv/run=2026-02-17/caiso_fuel_mix/year=2025/ ./data/caiso_fuel_mix/year=2025/ \
  --exclude "*" \
  --include "month=06/*" \
  --profile gridstatus

Sync everything at once:

aws s3 sync s3://gs-catalog-csv/run=2026-02-17/ ./data/ --profile gridstatus

The full export is approximately 1 TB (~1 million files).