m = scan_chronicle_metrics("./data", "2023/04/03").collect()
# create a temporary file
tf = tempfile.NamedTemporaryFile(suffix = ".parquet")
assert os.path.getsize(tf.name) == 0
z = write_parquet(m, tf)
assert os.path.getsize(tf.name) > 0
assert z is Noneio
File operations on chronicle parquet files
write_parquet
write_parquet (x:polars.dataframe.frame.DataFrame, filename:str)
Write chronicle data to parquet file
| Type | Details | |
|---|---|---|
| x | DataFrame | polars DataFrame |
| filename | str | Full file name |
| Returns | None |
get_s3_bucket_dates
get_s3_bucket_dates (bucket:str, type='logs', version='v1')
Get a list of dates for which there are chronicle logs or metrics in an S3 bucket
| Type | Default | Details | |
|---|---|---|---|
| bucket | str | S3 bucket name, without the “s3://” prefix | |
| type | str | logs | “logs” or “metrics” |
| version | str | v1 | “v1” or “v2” |
| Returns | list |
bucket = "colorado-posit-chronicle"
get_s3_bucket_dates(bucket, "metrics")