Skip to main content

afl-ai-utils

rm -rf build dist 
python3 setup.py sdist bdist_wheel
twine upload --repository pypi dist/* 

Installation

    pip install afl-ai-utils

Usage

Slack Alerting

from afl_ai_utils.slack_alerts import send_slack_alert 
send_slack_alert(info_alert_slack_webhook_url=None, red_alert_slack_webhook_url=None, slack_red_alert_userids=None, payload=None, is_red_alert=False)

    """Send a Slack message to a channel via a webhook.

Args:
    info_alert_slack_webhook_url(str): Infor slack channel url
    red_alert_slack_webhook_url(str): red alert channel url
    slack_red_alert_userids (list): userid's to mention in slack for red alert notification
    payload (dict): Dictionary containing Slack message, i.e. {"text": "This is a test"}
    is_red_alert (bool): Full Slack webhook URL for your chosen channel.

Returns:
    HTTP response code, i.e. <Response [503]>
"""

BigQuery Dataframe to BigQuery and get result in Datafeame

    def dump_dataframe_to_bq_table(self, dataframe: pd.DataFrame, schema_cols_type: dict, table_id: str, mode: str):

    >>> from afl_ai_utils.bigquery_utils import BigQuery
    >>> bq = BigQuery("keys.json")
    >>> bq.write_insights_to_bq_table(dataframe=None, schema=None, table_id=None, mode=None)
    
    
    """Insert a dataframe to bigquery

    Args:
        dataframe(pandas dataframe): for dataframe to be dumped to bigquery
        schema(BigQuery.Schema ): ex:
        schema_cols_type: {"date_start":"date", "id": "integer", "name": "string"}
        table_id (list): table_id in which dataframe need to be inserted e.g project_id.dataset.table_name = table_id
        mode(str): To append or replace the table - e.g mode = "append"  or mode="replace"
    Returns:
        returns as success message with number of inserted rows and table name
    """

Execute any query to BigQuery

    def execute_query(self, query):

    >>> from afl_ai_utils.bigquery_utils import BigQuery
    >>> bq = BigQuery("keys.json")
    >>> df = bq.execute_query(query = "SELECT * FROM TABLE")
    
    
    """
    Args:
        query (query of any type SELECT/INSERT/DELETE ) 
    Returns:
        returns dataframe of execute query result
    """

Metadata

Release files for afl-ai-utils 0.6.8

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for afl-ai-utils 0.6.8
File Size Uploaded Provenance
afl-ai-utils-0.6.8.tar.gz 20.5 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for afl-ai-utils 0.6.8
File Interpreter ABI Platform
afl_ai_utils-0.6.8-py3-none-any.whl Python 3 none any Details

Total release size: 44.9 kB

Release files / afl-ai-utils-0.6.8.tar.gz

Download URL afl-ai-utils-0.6.8.tar.gz
Size 20.5 kB
Tags Source
SHA-256 checksum
How to use checksums
522681c6c13818ae32bc933fc14ebc97a93c23bdeae09a64b6f2cab876e99378
BLAKE2b-256 checksum
How to use checksums
d83b3abb9f4a88f8779a28fc348407109767d2b28c8c7510ade1187caaaf62e1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.6

Release files / afl_ai_utils-0.6.8-py3-none-any.whl

Download URL afl_ai_utils-0.6.8-py3-none-any.whl
Size 24.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
de777673c3f92ba5bb464a2ed82d10cf2b76b3cffef4631a1f507ef355a58342
BLAKE2b-256 checksum
How to use checksums
5c9515f0579257382b6fb007f56dd77d94fe06b0ffc801e827f2579409043b2f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.9.6

Security for afl-ai-utils 0.6.8

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

0.6.8 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page