data-engineer-challenge | small prototype for an ETL

by MousaZeidBaker Shell Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | data-engineer-challenge Summary

data-engineer-challenge is a Shell library. data-engineer-challenge has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

You've been tasked with taking over a small prototype for an ETL (Extract - Transform - Load) pipeline, meant to ferry data from some services over into a Data Warehouse. The original author never finished the prototype, and they unfortunately also left very little documentation on how the prototype works! Part of this challenge is detective work, and so we've been intentionally vague in terms of describing how it works.

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Support

data-engineer-challenge has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

data-engineer-challenge has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of data-engineer-challenge is current.

Quality

data-engineer-challenge has no bugs reported.

Security

data-engineer-challenge has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

data-engineer-challenge does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

data-engineer-challenge releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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data-engineer-challenge Key Features

No Key Features are available at this moment for data-engineer-challenge.

data-engineer-challenge Examples and Code Snippets

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Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install data-engineer-challenge

You don't actually need any dependencies outside of Docker / Docker Compose, if you run the project that way. However, if you want to do local Python development also -- and perhaps be able to e.g., run pip install on new dependencies you need and then freeze them into the requirements.txt file, it's handy to do the following:. You can also install direnv. Each service folder contains a .direnv file with some default env variables, useful if you want to run the service outside Docker Compose.
Install pyenv
Install pyenv-virtualenv
Create a new Python 3.7.1 virtualenv: pyenv virtualenv 3.7.1 data-engineer-challenge
Activate the virtualenv: pyenv activate data-engineer-challenge

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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