"However, by posting Content using Service you grant us the right and license to use, modify, publicly perform, publicly display, reproduce, and distribute such Content on and through Service. You agree that this license includes the right for us to make your Content available to other users of Service, who may also use your Content subject to these Terms"
Does this mean I should have no expectation of privacy or control over anything I upload?
I mean, fundamentally, really consistent security is hard; and the best you can reasonably expect from someone you're not paying is "best effort". For them to make real promises about security opens them up to being sued if they fail; it's not really reasonable to ask someone to do that unless you're paying them a reasonable chunk of cash to offset that risk.
I don't see what security, paid vs. free or best-effort has got to do with my argument, which is that the loopholes in legalese are so hard to spot for anyone but a lawyer, that effectively my data might still be used in any way and possibly against my wishes or expectations (but which becomes legal when I consent to the PP and ToC).
Would you mind describing the kind of data you work with and which constraints you're subject to?
I have two questions:
- How do you handle incremental loads from files (or even google sheets)? Am I able to only load the diff, load full snapshots and get bi-temporality, etc?
- Are you supporting PostgREST as sponsors in any way? It's one of the most solid tools I've ever used, and I love to see that companies build great products on top of it!
- PostgREST is great. We are not sponsors at the moment, but looking to do this when we can!
pandas.concat and similar functions for appending to a Pandas dataframe can be quite slow. Just mentioning this in case you ever encounter this issue; maybe you don't need to. In my case I changed to dictionaries for important parts and 2 mins changed to 5 seconds execution time.
However, in my case, I have to change logical row structure and not just read in rows as is.
I can install a database on-prem and upload files to it and then I can too query it as if it was in a database.
From what I've seen on the this seems like a fancy cloud database client.
We're happy to introduce Dropbase 2.0! It's a tool that helps you bring offline files, such as CSV, Excel, and JSON files, into Postgres database. You can also process your data before uploading it using a spreadsheet-like interface or by writing a custom Python script. Once your data is in the database, you can query it using any third party tool (credentials will be provided). You can also access your data via REST API (powered by PostgREST) or create custom endpoints to serve a more specific use case.
A bit about the tech:
Currently, we support .csv, .json, .xls, .xlsx files. For data processing, we use Pandas, so if you are comfortable using Python, you can write your own custom functions to process the data. We also give you a free shared Postgres database to test the tool with (your data is isolated and hidden from others). Each one of these databases come with an instance of PostgREST preinstalled, so you can query your database using REST API ([http://postgrest.org/en/v7.0.0/](http://postgrest.org/en/v7....). You can also generate an access token with an expiry date to share your data with others.
There are many more features that we baked into the product. Come check it out, it's open for HN community.