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"""
Reads a list of CSV files located in an S3 bucket.
"""
import getml.communication as comm
from .connection import Connection
[docs]def read_s3(
name,
bucket,
keys,
region,
sep=",",
num_lines_read=0,
skip=0,
colnames=None,
conn=None,
):
"""
Reads a list of CSV files located in an S3 bucket.
Example:
Let's assume you have two CSV files - *file1.csv* and
*file2.csv* - in the bucket. You can
import their data into the getML engine using the following
commands:
>>> getml.engine.set_s3_access_key_id("YOUR-ACCESS-KEY-ID")
>>>
>>> getml.engine.set_s3_secret_access_key("YOUR-SECRET-ACCESS-KEY")
>>>
>>> stmt = data.database.sniff_s3(
... bucket="your-bucket-name",
... keys=["file1.csv", "file2.csv"],
... region="us-east-2",
... name="MY_TABLE",
... sep=';'
... )
>>>
>>> getml.database.execute(stmt)
>>>
>>> stmt = data.database.read_s3(
... bucket="your-bucket-name",
... keys=["file1.csv", "file2.csv"],
... region="us-east-2",
... name="MY_TABLE",
... sep=';'
... )
You can also set the access credential as environment variables
before you launch the getML engine.
Args:
name (str):
Name of the table in which the data is to be inserted.
bucket (str):
The bucket from which to read the files.
keys (List[str]):
The list of keys (files in the bucket) to be read.
region (str):
The region in which the bucket is located.
sep (str, optional):
The separator used for separating fields. Default:`,`
num_lines_read (int, optional):
Number of lines read from each file.
Set to 0 to read in the entire file.
skip (int, optional):
Number of lines to skip at the beginning of each
file (Default: 0).
colnames(List[str] or None, optional):
The first line of a CSV file
usually contains the column names. When this is not the case, you need to
explicitly pass them.
conn (:class:`~getml.database.Connection`, optional):
The database connection to be used.
If you don't explicitly pass a connection,
the engine will use the default connection.
"""
# -------------------------------------------
conn = conn or Connection()
# -------------------------------------------
# Prepare command.
cmd = dict()
cmd["name_"] = name
cmd["type_"] = "Database.read_s3"
cmd["bucket_"] = bucket
cmd["keys_"] = keys
cmd["num_lines_read_"] = num_lines_read
cmd["region_"] = region
cmd["sep_"] = sep
cmd["skip_"] = skip
cmd["conn_id_"] = conn.conn_id
if colnames is not None:
cmd["colnames_"] = colnames
# -------------------------------------------
# Send JSON command to engine.
comm.send(cmd)