Q. Which assertion library should I use with Mocha?
A: Mocha doesn’t bundle an assertion library, so you can choose from many options like Chai, Should.js, Unexpected, or built-in Node assert. The blog example uses basic assertions in the browser environment. Using Chai gives expressive style (e.g. expect(value).to.equal(…)).
Q. How do I write synchronous and asynchronous test cases?
A: For synchronous tests: use describe and it blocks and assertions (e.g. assert.equal(…)). For asynchronous tests: provide a done callback or return a Promise. Mocha waits for done() or Promise resolution. The blog shows adding timeouts (e.g. via this.timeout(…)) to handle delays.
Q. How do I set up Mocha to test my code?
A: You can install Mocha locally or globally via npm (npm install mocha –save-dev). In the project, you create test files (commonly under a test/ folder). The blog demonstrates using StackBlitz to quickly create HTML, index.js, and test code. You import Mocha (via CDN or local install), then call mocha.run() in the browser or run […]
Q. What is Mocha and why use it for JavaScript testing?
Answer: Mocha is a flexible, feature-rich JavaScript test framework that works both in Node.js and in browsers. It supports synchronous and asynchronous tests, integrates with any assertion library (e.g. Chai), and offers custom reporters and hooks. Using Mocha helps structure test cases, improves maintainability, and makes automated testing more reliable.
Q. How to secure access to S3 and manage credentials in Airflow?
A: Do not hardcode AWS credentials; use IAM roles or AWS Secrets Manager. In Airflow, configure a connection (via AWS connection) or use assume_role or profile_name. Ensure minimal S3 permissions: allow only read/write to the specific bucket or prefix. Use HTTPS for transfers. Optionally enable S3 server-side encryption (SSE) or client-side encryption.
Q. In what format should I store data in S3, and how do I partition it?
A: Choose a format based on your downstream needs (CSV, JSON, Parquet, Avro). Parquet is efficient for analytics. Partition data by date (e.g., year=2025/month=09/day=24/…) for fast retrieval. Use robust naming conventions, avoid overly nested paths, and be consistent.
Q. How do I deal with API pagination, rate limiting, and errors in Airflow?
A: Pagination: in the extract task, page through API endpoints (by cursor/offset) until done. Rate limiting: respect API limits by inserting sleep delays, using backoff strategies, or using token buckets. Errors: wrap HTTP calls in try/except (or equivalent in your operator), catch timeouts, status codes, and use Airflow retries. Also consider circuit-breaker logic if API […]
Q. Why use Airflow for such ETL tasks instead of writing a simple script?
A: Airflow provides: scheduling (cron-like) dependencies between tasks retry, failure handling, monitoring modular DAG definitions ability to scale, parallelize, monitor logs, alert on failures integration with many systems (APIs, S3, databases). Thus, as projects grow, Airflow is preferable for robustness and maintainability.
Q. What does ETL API data to S3 mean?
A: ETL stands for Extract, Transform, Load. Here: Extract: fetch data from a remote HTTP API (e.g. REST) Transform: possibly parse, filter, clean, aggregate or reformat the data Load: store the transformed data as files (e.g. JSON, CSV, Parquet) in an AWS S3 bucket Using Airflow automates and schedules this pipeline.
Q. What security pitfalls should I watch out for?
A: Reusing IVs (especially in CTR/GCM) is catastrophic. Using weak keys or passwords without proper key derivation (use PBKDF2 / scrypt / Argon2). Ignoring authentication (don’t use plain AES-CBC without HMAC or use GCM). Hardcoding keys or secrets in code. Leaking crypto errors. Not checking ciphertext length or format before decrypting (to avoid padding oracle […]