semvec/pypi-packages huggingface dataset:
gdal2mbt 0.4.1
Create MBTiles from GDAL files.
License: MIT
Keywords: gdal,mbtiles,gis,tms

# gdal2mbt

*Create MBTiles from a GDAL file*

## Requirements

- Python 2.7

## Installation

```
pip install https://github.com/icetan/gdal2mbt/archive/master.zip
```

Or from source

```
git clone https://github.com/icetan/gdal2mbt.git
pip install -e gdal2mbt
```

## Creating a MBTile file

```sh
gdal2mbt create goteborg.mbtiles 8 goteborg.vrt
```

Or use a JSON config file with an optional metadata dictionary that will
overwrite the defaults in the MBTiles metadata table.

```json
{
    "source": "goteborg.vrt",
    "num_levels": 8,
    "metadata": {
        "name": "goteborg",
        "description": "Aerial photos over Göteborg city"
    }
}
```

```sh
gdal2mbt create -c goteborg.json goteborg.mbtiles
```

To resume an aborted MBTiles creation process pass the `-r` flag to `create`.

## Parallel jobs

Speed up MBTiles creation by distributing the load over several processors or
even computers by using [GNU Parallel](http://www.gnu.org/software/parallel/).

Create an MBTiles file for each tile on zoom level 0, this will depend on the
second argument which defines how many zoom levels to generate in total.

```sh
gdal2mbt config goteborg.vrt 6 | parallel gdal2mbt create -c
```

Merge all the created MBTiles to one.

```sh
gdal2mbt merge goteborg.mbtiles goteborg.*.mbtiles
```

Or to squash all MBTiles into one to save space use the destructive `-s` flag
which will remove each merged MBTiles file.

```sh
gdal2mbt merge -s goteborg.*.mbtiles
```

Add zoom levels that might have been omitted due to the amount of tiles on zoom
level 0 at time of creation.

```sh
gdal2mbt levels goteborg.mbtiles 8
```
kevlar 0.0.8
Kevlar will be something cool
License: MIT

kevlar
======

Kevlar is an API regression testing framework. It uses a black-box testing methodology to ensure you maintain perfect backwards compatibility as your API evolves.

Tagline
-------
> Keep your API bulletproof.

Installation
------------

It's in Python, so pip is the way to go:

    pip install kevlar

Usage
-----

There are two phases when using kevlar: 1) establishing a baseline and 2) regression testing and accepting/rejecting behavior changes.

First, you define a set of API requests to be made against an API. After kevlar runs your test suite, you'll carefully review and generalize the responses it recieved back to make sure they're exactly what you're expecting.

After you've established a baseline, run the test suite on every commit, push, build, or even on an hourly cron job that'll test production to make sure absolutely nothing has changed in what you're responding to your clients with. Since APIs evolve and grow overtime, adapt your baseline as appropriate whenever you add new functionality or have differences reported from kevlar.

### Why?

Because manual smoke testing an API is really painful. It's meant to be consumed by a machine, so let a machine do your smoke testing for you! ʕノ•ᴥ•ʔﾉ*:･ﾟ✧

### Is it any good?

:thumbsup: