Pandas VS Airflow

Pandas is a go-to tool for tabular data management, processing, and analysis in Python, but sometimes you may want to go from pandas to SQL.

panda’s

> The big thing pandas has going for it is that it's already been through this field testing. All the bugs have been ironed out by the hundreds of thousands of users.

At this very moment pandas github repo has 1563 open issues labeled with a bug tag [0]. So much for "all the bugs have been ironed out".

[0] https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3...

Python is the main programming language I use nowadays. In particular numpy and pandas are of course extremely useful. I also use biopython package - a collection of software tools for biological computation written in Python by an international group of researchers and developers.

Below is the python Task that transforms the tweets list into a Pandas dataframe, then dumps it in our MinIO Object Storage as a CSV file:

It was rewarding to dig into SQLite a bit while solving this puzzle, so I figured this would be a good opportunity to learn a bit more about pandas too! So how would I adapt this working SQL solution to pandas?

All the data has been extracted from the official Tor Metrics website, and using Python with the Pandas library I've cleaned the data. Finally, the visualizations have been made with Tableau.

If you did that you could use a built-in library like csv to read and parse the file or you could use a 3rd party library like Pandas. Alternatively, you could store your file as json:

💡 You can read more here.

Its a bit overkill but i use Airflow with local executor.

To learn more about it, I built a Data Pipeline that uses Apache Airflow to pull Elon Musk tweets using the Twitter API and store the result in a CSV stored in a MinIO (OSS alternative to AWS s3) Object Storage bucket.

Airflow

I am currently having a problem with trying to enable Azure OAuth to authenticate into our airflow instance. I have posted in countless other places trying to get answers so this is my next place I am trying. Here is the link to the discussion I posted within the airflow repo: https://github.com/apache/airflow/discussions/28098 but I will also do the liberty of posting it here as well. If anybody has any knowledge or can help I would greatly appreciate it as I have been dealing with this for over a month with no answers.

Airflow is really popular, started at Airbnb. Pros: huge community, super mature. Cons: generic workflow orchestration, not the best for handling only data, hard to scale and maintain.

Airflow might also be a good option for you. Essentially DAGs of cronjobs. We like it a lot.

$ helm upgrade --install airflow apache-airflow/airflow --namespace airflow --create-namespace Release "airflow" does not exist. Installing it now. NAME: airflow LAST DEPLOYED: Sun Nov 6 02:06:55 2022 NAMESPACE: airflow STATUS: deployed REVISION: 1 TEST SUITE: None NOTES: Thank you for installing Apache Airflow 2.4.1! Your release is named airflow. You can now access your dashboard(s) by executing the following command(s) and visiting the corresponding port at localhost in your browser: Airflow Webserver: kubectl port-forward svc/airflow-webserver 8080:8080 --namespace airflow Default Webserver (Airflow UI) Login credentials: username: admin password: admin Default Postgres connection credentials: username: postgres password: postgres port: 5432 You can get Fernet Key value by running the following: echo Fernet Key: $(kubectl get secret --namespace airflow airflow-fernet-key -o jsonpath="{.data.fernet-key}" | base64 --decode) ########################################################### # WARNING: You should set a static webserver secret key # ########################################################### You are using a dynamically generated webserver secret key, which can lead to unnecessary restarts of your Airflow components. Information on how to set a static webserver secret key can be found here: https://airflow.apache.org/docs/helm-chart/stable/production-guide.html#webserver-secret-key

I gotta admit, my first thought was "Duct Size" is a weird name for a distributed work-flow tool[1].

[1] https://airflow.apache.org/