docs/async_examples.rst

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.. _async_examples_of_usage:

============================
Asynchronous client examples
============================
File: `async_key_value.py`_.

Basic usage
-----------
Asynchronous client and cache (:py:class:`~pyignite.aio_client.AioClient` and :py:class:`~pyignite.aio_cache.AioCache`)
has mostly the same API as synchronous ones (:py:class:`~pyignite.client.Client` and :py:class:`~pyignite.cache.Cache`).
But there is some peculiarities.

Basic key-value
===============
Firstly, import dependencies.

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  :language: python
  :lines: 18

Let's connect to cluster and perform key-value queries.

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Scan
====
The :py:meth:`~pyignite.aio_cache.AioСache.scan` method returns :py:class:`~pyignite.cursors.AioScanCursor`,
that yields the resulting rows.

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  :language: python
  :dedent: 8
  :lines: 39-50

ExpiryPolicy
============
File: `expiry_policy.py`_.

You can enable expiry policy (TTL) by two approaches.

Firstly, expiry policy can be set for entire cache by setting :py:attr:`~pyignite.datatypes.prop_codes.PROP_EXPIRY_POLICY`
in cache settings dictionary on creation.

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  :language: python
  :dedent: 12
  :lines: 73-76

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Secondly, expiry policy can be set for all cache operations, which are done under decorator. To create it use
:py:meth:`~pyignite.cache.BaseCache.with_expire_policy`

.. literalinclude:: ../examples/expiry_policy.py
  :language: python
  :dedent: 12
  :lines: 97-106

Transactions
------------
File: `transactions.py`_.

Client transactions are supported for caches with
:py:attr:`~pyignite.datatypes.cache_config.CacheAtomicityMode.TRANSACTIONAL` mode.
**Supported only python 3.7+**

Let's create transactional cache:

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  :dedent: 8
  :lines: 30-33

Let's start a transaction and commit it:

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Let's check that the transaction was committed successfully:

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Let's check that raising exception inside `async with` block leads to transaction's rollback

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Let's check that timed out transaction is successfully rolled back

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See more info about transaction's parameters in a documentation of :py:meth:`~pyignite.aio_client.AioClient.tx_start`

SQL
---
File: `async_sql.py`_.

First let us establish a connection.

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  :language: python
  :dedent: 4
  :lines: 197-198

Then create tables. Begin with `Country` table, than proceed with related
tables `City` and `CountryLanguage`.

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  :language: python
  :lines: 25-42, 51-59, 67-74

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Create indexes.

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Fill tables with data.

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Now let us answer some questions.

What are the 10 largest cities in our data sample (population-wise)?
====================================================================

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  :language: python
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  :lines: 225-243

The :py:meth:`~pyignite.aio_client.AioClient.sql` method returns :py:class:`~pyignite.cursors.AioSqlFieldsCursor`,
that yields the resulting rows.

What are the 10 most populated cities throughout the 3 chosen countries?
========================================================================

If you set the `include_field_names` argument to `True`, the
:py:meth:`~pyignite.client.Client.sql` method will generate a list of
column names as a first yield. Unfortunately, there is no async equivalent of `next` but
you can await :py:meth:`__anext__()`
of :py:class:`~pyignite.cursors.AioSqlFieldsCursor`

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  :dedent: 8
  :lines: 246-271

Display all the information about a given city
==============================================

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Finally, delete the tables used in this example with the following queries:

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.. _expiry_policy.py: https://github.com/apache/ignite-python-thin-client/blob/master/examples/expiry_policy.py
.. _async_key_value.py: https://github.com/apache/ignite-python-thin-client/blob/master/examples/async_key_value.py
.. _async_sql.py: https://github.com/apache/ignite-python-thin-client/blob/master/examples/async_sql.py
.. _transactions.py: https://github.com/apache/ignite-python-thin-client/blob/master/examples/transactions.py