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awsdf
Advanced tools
awsdf package
This module enables connecting to AWS and extracting metadata in pandas dataframes.
Installing from PyPI: pip install -U awsdf
USAGE:
import awsdf
aws_account = awsdf.Account(profile_name=”<PROFILE_NAME>”)
glue_databases_df = aws_account.glue_get_databases()
class awsdf.aws.Account(aws_access_key_id=None, aws_secret_access_key=None, aws_session_token=None, region_name=None, profile_name=None)
Instantiate class object for connecting to AWS and retriving metadata from AWS
init(aws_access_key_id=None, aws_secret_access_key=None, aws_session_token=None, region_name=None, profile_name=None)
Provide access keys OR Profile name to connect to AWS account.
Keys take preceedence
**Parameters:**
*aws_access_key_id (string) – AWS access key ID*
*aws_secret_access_key (string) – AWS secret access key*
*aws_session_token (string) – AWS temporary session token*
*region_name (string) – AWS region*
*profile_name (string) – AWS profile name*
glue_get_jobs() -> DataFrame
Get AWS Glue jobs
Returns:
dataframe
glue_get_job_history(job_name, no_of_runs=1) -> DataFrame
Retrieve glue job history
Arguments:
job_name – Name of job to retrive history
Keyword Arguments:
no_of_runs – No of runs to retrive in descending order
(default: {1})
Returns:
dataframe
glue_get_databases() -> DataFrame
Get AWS Glue jobs
Returns:
dataframe
glue_get_tables(dbname=None) -> DataFrame
Get AWS Glue tables
Keyword Arguments:
dbname – Database Name for which to retrieve tables (default:
{None})
Returns:
dataframe
glue_get_fields(dbname, tablename) -> DataFrame
Get AWS Glue table columns
Keyword Arguments:
dbname – Database Name for table tablename – Database Name
for which to retrieve columns
Returns:
dataframe
athena_execute_query(database: str, query: str, s3_output: str | None = None, use_cache: bool = True)
Execute athena query
Arguments:
database – Database name query – Query to execute
Keyword Arguments:
s3_output – Amazon S3 path for query output (optional)
use_cache – Use cached results if any (default: {True})
Returns:
dataframe
Raises:
ValueError – If s3_output is provided but is not a valid S3
URI
athena_data_dictionary(include_dbs: list = [], exclude_dbs: list = []) -> DataFrame
Get AWS Athean data dictionary. A data frame with all databases,
tables & fields with datatypes
Keyword Arguments:
include_dbs (optional) – list of databases to be included
exclude_dbs (optional) – list of databases to be excluded if
include_dbs list is empty.
Returns:
dataframe
quicksight_get_datasources() -> DataFrame
Get QuickSight datasources
Keyword Arguments:
N/A
Returns:
dataframe
quicksight_get_datasets(includeDetails: bool = False) -> DataFrame
Get QuickSight datasets
Keyword Arguments:
includeDetails (optional) – Include addition details i.e.
ConsumedSpiceCapacityInBytes & Owner. Default=False
Returns:
dataframe
quicksight_get_dataset_permissions(AwsAccountId: str, DataSetId: str)
Get QuickSight dataset permissions
Keyword Arguments:
AwsAccountId – AWS account id DataSetId – Dataset id
Returns:
dataframe
quicksight_get_dataset_details(datasetId: str) -> dict
Get QuickSight dataset details
Keyword Arguments:
DataSetId – Dataset id
Returns:
dataframe
quicksight_get_dashboards(includeDetails: bool = False) -> DataFrame
Get QuickSight dashboards
Keyword Arguments:
includeDetails (optional) – **NOT IMPLEMENTED** Include
addition details. Default=False
Returns:
dataframe
quicksight_get_dashboard_details(dashboardId: str) -> dict
Get QuickSight dashboard details
Keyword Arguments:
dashboardId – Dashboard id
Returns:
dictionary
kms_encrypt(plaintext: str, key_id: str) -> str
Encrypt a plaintext string using AWS KMS and return
base64-encoded ciphertext.
Parameters:
plaintext (str): The string to encrypt. key_id (str): The KMS
key ARN or ID.
Returns:
str: base64-encoded ciphertext
kms_decrypt(ciphertext_b64: str) -> str
Decrypt a base64-encoded ciphertext string using AWS KMS and
return the plaintext.
Parameters:
ciphertext_b64 (str): base64-encoded ciphertext
Returns:
str: decrypted plaintext string
get_secret_from_secrets_manager(secret_name: str) -> dict
Retrieve a secret value from AWS Secrets Manager.
Parameters:
secret_name (str): The name or ARN of the secret.
Returns:
str: The secret string value.
Raises:
ClientError: If retrieval fails due to permission or
configuration issues.
FAQs
AWS metadata as dataframes
We found that awsdf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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