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diff --git a/ANNOUNCE.md b/ANNOUNCE.md
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+# Announcing datasette-connectors 0.25
+
+## What's new
+
+This is the first release of datasette-connectors, derived from the [Datasette](https://github.com/simonw/datasette) fork for supporting [Datasette-Pytables](https://github.com/PyTables/datasette-pytables).
+
+## What it is
+
+[Datasette](https://github.com/simonw/datasette) is a Python module which provides a web interface and a JSON API for SQLite files. But, in conjuntion with Datasette-Connectors, it 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-connectors/blob/master/DEVELOPERS.md)).
+
+## Resources
+
+Visit the main datasette-connectors site repository at:
+https://github.com/PyTables/datasette-connectors
+
+----
+
+  **Enjoy data!**

diff --git a/DEVELOPERS.md b/DEVELOPERS.md
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+# How to make connectors for other data sources?
+
+With Datasette-Connectors you can use [Datasette](https://github.com/simonw/datasette) for publishing data in your own format, not only SQLite, to the Internet with a JSON API. For this, you have to make connectors using the interface that is described here.
+
+## Tables inspection
+
+First of all, you need to implement a special method called `inspect` that receives the path of the file as an argument and returns a tuple formed by a dictionary with tables info, a list with views name and a string identifying the connector. Each entry in the dictionary for tables info has the next structure:
+
+    tables['table_name'] = {
+        'name': 'table_name',
+        'columns': ['c1', 'c2'],
+        'primary_keys': [],
+        'count': 100,
+        'label_column': None,
+        'hidden': False,
+        'fts_table': None,
+        'foreign_keys': {'incoming': [], 'outgoing': []}
+
+This structure is used in [Datasette-PyTables](https://github.com/PyTables/datasette-pytables). In your case, you may need additional entries like primary keys or foreign keys.
+
+## Returning results
+
+Datasette uses SQL for specifying the queries, so your connector has to accept SQL and execute it. The next class and methods are needed:
+
+    class Connection:
+        def __init__(self, path):
+            ...
+
+        def execute(self, sql, params=None, truncate=False, page_size=None, max_returned_rows=None):
+            ...
+
+The `Connection.execute()` method receives:
+
+* **sql**: the query
+* **params**: a dictionary with the params used in the query
+* **truncate**: a boolean saying if the returned data can be separated in pages or not
+* **page_size**: the number of rows a page can contain
+* **max_returned_rows**: the maximum number of rows Datasette expects
+
+Probably, you'll need to parse the SQL query if your data container has its own style for queries, but other databases could work with the SQL queries without requiring any parsing.
+
+Note: Sometimes, Datasette make queries to `sqlite_master`; you need to keep it in mind.
+
+The `Connection.execute()` method has to return a tuple with:
+
+* a list of rows (Datasette expects something similar to SQLite rows)
+* a boolean saying if the data is truncated, i.e., if we return all the rows or there are more rows than the maximum indicated in max_returned_rows
+* a tuple with the description of the columns in the form `(('c1',), ('c2',), ...)`
+
+## Rows format
+
+Datasette receives the results from the queries with SQLite row instances, so you need to return your rows in a similar way.
+
+For example, if you have the next query:
+
+    SELECT name FROM persons
+
+you need to return an object that allows to do things like:
+
+    row[0] == 'Susan'
+    row['name'] == 'Susan'
+    [c for c in row] == ['Susan']
+    json.dumps(row)
+
+For example, you can extend the `list` object to get it, but as long as you implement a similar interface, you can develop your own implementation too.

diff --git a/LICENSE b/LICENSE
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diff --git a/MANIFEST.in b/MANIFEST.in
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+include README.md
+include VERSION

diff --git a/README.md b/README.md
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+# datasette-connectors
+
+[Datasette](https://github.com/simonw/datasette) is a Python module which provides a web interface and a JSON API for SQLite files. But, in conjuntion with Datasette-Connectors, it 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-connectors/blob/master/DEVELOPERS.md)).
+
+## Installation
+
+Run `pip install datasette-connectors` to install both Datasette and Datasette-Connectors. Easy as pie!
+
+## Usage
+
+You can use Datasette from the console in the traditional way:
+
+    datasette serve path/to/data.h5
+
+This will start a web server on port 8001; then you can access to your data visiting [http://localhost:8001/](http://localhost:8001/)
+
+Or you can use Datasette in your own Python programs:
+
+    from datasette_connectors import monkey; monkey.patch_datasette()
+    from datasette_connectors import connectors; connectors.load()
+
+For that, you need to patch the original Datasette and load the external connectors.
+
+Read the [Datasette documentation](http://datasette.readthedocs.io/en/latest/) for more advanced options.

diff --git a/RELEASE_NOTES.md b/RELEASE_NOTES.md
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+# Release notes for datasette-connectors
+
+
+## Initial version 0.25
+
+* Compatible with Datasette 0.25
+
+* Basic API for external connectors.

diff --git a/RELEASING.md b/RELEASING.md
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+# Releasing datasette-connectors
+
+Author: Javier Sancho, Francesc Alted
+Contact: jsf@jsancho.org, francesc@blosc.org
+Date: 2018-10-04
+
+
+## Preliminaries
+
+* Update the version number at ``VERSION`` and ``ANNOUNCE.md``.
+
+* Make sure that ``RELEASE_NOTES.md`` and ``ANNOUNCE.md`` are up to
+  date with the latest news in the release.
+
+* Commit your changes:
+
+```
+    $ git commit -a -m"Getting ready for X.Y.Z final"
+```
+
+* Once a year: check that the copyright year in `LICENSE` file.
+
+
+## Tagging
+
+* Create a tag ``vX.Y.Z`` from ``master``.  Use the next message:
+
+```
+    $ git tag -a vX.Y.Z -m "Tagging version X.Y.Z"
+```
+
+  Note: For release candidates, just add a rcN suffix to tag ("vX.Y.ZrcN").
+
+* Or, alternatively, make a signed tag (requires gpg correctly configured):
+
+```
+    $ git tag -s vX.Y.Z -m "Tagging version X.Y.Z"
+```
+
+* Push the tag to the Github repo:
+
+```
+    $ git push
+    $ git push --tags
+```
+
+* Do the official release.  Go to:
+
+https://github.com/PyTables/datasette-connectors/releases/edit/vX.Y.Z
+
+and add the title for the release (vX.Y.Z) and the release notes there.
+
+
+## Testing
+
+* Go to the root directory and run:
+
+```
+    $ pytest
+```
+
+
+## Packaging
+
+* Make sure that you are in a clean directory.  The best way is to
+  re-clone and re-build:
+
+```
+  $ cd /tmp
+  $ git clone https://github.com/PyTables/datasette-connectors
+  $ cd datasette-connectors
+  $ python setup.py build
+  $ pytest
+```
+
+* Make the tarball with the command:
+
+```
+  $ python setup.py sdist
+```
+
+Do a quick check that the tarball is sane.
+
+
+## Uploading
+
+* Upload it also in the PyPi repository:
+
+```
+    $ python setup.py sdist upload
+```
+
+
+## Announcing
+
+* Send an announcement to the pytables-announce, pytables-users and pydata
+  lists.  Use the ``ANNOUNCE.md`` file as skeleton (or possibly as
+  the definitive version).
+
+* Tweet about the new release and rejoice!
+
+
+## Post-release actions
+
+* Create new headers for adding new features in ``RELEASE_NOTES.rst``
+  and add this place-holder instead:
+
+  #XXX version-specific blurb XXX#
+
+* Update ``VERSION`` file to X.Y.(Z+1)-dev
+
+* Commit your changes with:
+
+```
+  $ git commit -a -m"Post X.Y.Z release actions done"
+```
+
+
+That's all folks!