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Need a quickstart! #10
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Hey Element, thanks for opening the issue, sorry I just now noticed! I've been hesitant to write the README but it's about time I clean it up as we're nearing a beta release. I'm having trouble clearly conveying the usages for Meerschaum in a single README. But minimal usage would look something like the following:
I think I need an FAQ for the available I'm planning on having a dashboard that interacts with the API like the CLI does, but frontend development is not my specialty. Maybe I should make tutorials? Documentation can be overwhelming. |
No worries, feel free to call me Casey, we spoke this past sunday at the LUP LUG. I think a minimal example from zero to your first pipe would be useful.
Any info I can provide you to help debug this failure? I'm using the docker-compose and docker install that came with Pop OS 20.04. Your readme suggests installing docker-compose from pip but I have not done so: if you have a strict dependency on a particular docker-compose version you should maybe seek to keep that as a pip dependency, no? Moreover, I think it's really important that the README give us a clear example of the usefulness of this tool. As written, it says the following:
Cool. Where can these time-series data streams come from? Where can they go to? I see some code for a SQL connector and you mentioned this was an ETL tool in our talk on Sunday, but are there already other existing sources and sinks? I think the really critical thing is that, cool shell UI or cool web UI aside (I'd hold off on the web UI), once I have your package installed I have zero idea how to use it to extract, transform, or load data. Even the toyest of the toy examples would go a long way to showing how this tool is unique or useful. Let's suppose I have... a sqlite3 db with a table full of student names, submission datetimes, and grades, and I'd like to extract it, apply some hashing function to the student name column, and dump out a csv of "anonymized" data. How? (Is my supposition dumb? Is there a better scenario where this tool shines?) |
Hey Casey, thanks for the detailed post. I can't believe it took this long to find out, but the code for taking input to yes/no questions was just broken. I hadn't tested it properly, so answering I've also changed the default version in the docker-compose.yaml file from Try upgrading to version 0.0.39 which should address these issues.
To address the README question, the current use case for Meerschaum is helping non-system engineers spin up a pre-configured Grafana/TimescaleDB stack and migrate outside data into TimescaleDB (particularly in the case of utilities data). The plan is to implement the In your example
The The The
This will open your editor and allow you to edit the parameters of the Pipe. Your parameters would look something like this:
Here's one way to register a Pipe from a script instead (does the same as above):
I hope this wasn't too complicated. I think of it as a framework for non-system engineers who need to build visualizations for large sets of time-series data. There are a lot of pieces to get into, like how the API works and how Connectors work (SQLConnector vs APIConnector vs other types to come), but overall Pipes are a way to simplify many different connection types and organize data. Thank you for taking interest in Meerschaum! It's exciting to answer GitHub issues and I hope I get more feedback in the future. If you have any further issues (and be warned, you'll probably run into a few bugs), feel free to reach out here or at my email bennett.meares@gmail.com or on Discord (bennett#0708). I'm still getting used to Mumble and Matrix, but I hope to join in on more LUP LUGs. Everyone was so nice, and I look forward to meeting more Linux nerds like me. |
Hi Bennett! I see on your dev branch that you have a header for a quick start, but no content there. Want some help writing something here? What's a minimal usage of this package look like? :)
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