anna-anisienia

import pyodbc
import pandas as pd

df = pd.read_csv('myfile.csv')
MY_TABLE = 'some_tbl'

conn = pyodbc.connect(driver='{ODBC Driver 17 for SQL Server}',
                      server='MYSERVER',
                      database='MYDB',
                      uid='MYUSER', pwd='MYPASSWORD')

anna-anisienia

"""
Dataset used: https://datasets.wri.org/dataset/globalpowerplantdatabase
"""
import os
import time
import pandas as pd
from datetime import datetime, timedelta
import awswrangler as wr
from boto3.dynamodb.conditions import Key

anna-anisienia

import boto3
import uuid
import json
import random
import logging
from datetime import datetime

logging.basicConfig(format="[%(levelname)s] [%(name)s] [%(asctime)s]: %(message)s",
                    level="INFO")
logger = logging.getLogger(__name__)

anna-anisienia

# set a base image that includes Lambda Runtime API: 
# Source: https://hub.docker.com/r/amazon/aws-lambda-python
FROM amazon/aws-lambda-python:3.8

# optional: ensure that pip is up to date
RUN /var/lang/bin/python3.8 -m pip install --upgrade pip

# first we COPY only requirements.txt to ensure that later builds
# with changes to your src code will be faster due to caching of this layer
COPY requirements.txt .

anna-anisienia

from airflow.models import DagModel, TaskInstance, DagRun
from airflow.utils.decorators import apply_defaults
from airflow.operators.dagrun_operator import TriggerDagRunOperator
from airflow.sensors.base_sensor_operator import BaseSensorOperator
from airflow.utils.db import provide_session


class WaitForCompletion(BaseSensorOperator):
    """
    Waits for a different DAG or a task in a different DAG to complete

anna-anisienia

import json
import logging
import requests
import pandas as pd
import awswrangler as wr
from typing import List, Any


class DataQualityAlert:
    def __init__(self, slack_webhook_url: str, database: str = "ecommerce"):

anna-anisienia

import boto3
import uuid
import json
import random
import logging
from datetime import datetime

logging.basicConfig(format="[%(levelname)s] [%(name)s] [%(asctime)s]: %(message)s",
                    level="INFO")
logger = logging.getLogger(__name__)

anna-anisienia

import requests
import boto3
import uuid
import time
import json

client = boto3.client('kinesis', region_name='eu-central-1')
partition_key = str(uuid.uuid4())

anna-anisienia

# set a base image: https://hub.docker.com/_/python?tab=tags&page=1&ordering=last_updated
FROM python:3.8

# optional: ensure that pip is up to date
RUN pip install --upgrade pip

# first we COPY only requirements.txt to ensure that later builds
# with changes to your src code will be faster due to caching of this layer
COPY requirements.txt .
RUN pip install -r requirements.txt

anna-anisienia

import time
import requests
import logging
import boto3
from botocore.config import Config


def send_price_data_to_timestream(write_client):
    base_url = "https://min-api.cryptocompare.com/data"
    symbols = "BTC,ETH,REP,DASH"