X-Git-Url: https://git.jsancho.org/?p=datasette-pytables.git;a=blobdiff_plain;f=README.md;h=57e027049ead7f5689b7bdb576d46d5b8ded94bd;hp=a447c04e834a0768199862ea71ec6c1de6664ec3;hb=30d9dbfca20886a04bdbc6da0df77afb16e26436;hpb=f2e02a0f692b0312c7e9e1051ff0cca6205b4972

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+[![Build Status](https://travis-ci.org/PyTables/datasette-pytables.svg?branch=master)](https://travis-ci.org/PyTables/datasette-pytables)
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 # datasette-pytables
 
-Datasette-PyTables provides a web interface and a JSON API for [PyTables](https://github.com/PyTables/PyTables) files, allowing them to be accessible for e.g. Javascript programs. It works in conjunction with [Datasette-Core](https://github.com/PyTables/datasette-core), a trivial fork of the original [Datasette](https://github.com/simonw/datasette), which provides a web interface for SQLite files.  This fork is able to work with SQLite files, like the original project, but can accept external connectors for any kind of database files, so you can develop your own connector for your favourite data container if you want (read [developers doc](https://github.com/PyTables/datasette-pytables/blob/master/DEVELOPERS.md))
+Datasette-PyTables provides a web interface and a JSON API for [PyTables](https://github.com/PyTables/PyTables) files, allowing them to be accessible for e.g. Javascript programs. It works in conjunction with [Datasette-Core](https://github.com/PyTables/datasette-core), a trivial fork of the original [Datasette](https://github.com/simonw/datasette), which provides a web interface for SQLite files.  This fork is able to work with SQLite files, like the original project, but can accept external connectors for any kind of database files, so you can develop your own connector for your favourite data container if you want (read [developers doc](https://github.com/PyTables/datasette-pytables/blob/master/DEVELOPERS.md)).
 
 ## Installation
 
@@ -13,3 +16,7 @@ Run `pip install datasette-pytables` to install both the forked version of Datas
 This will start a web server on port 8001; then you can access to your data visiting [http://localhost:8001/](http://localhost:8001/)
 
 Read the [Datasette documentation](http://datasette.readthedocs.io/en/latest/) for more advanced options.
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+See how a typical Table query looks like in the Datasette-PyTables web interface:
+
+![Datasette Screenshot](/images/Datasette-Screenshot.png)