معرفی شرکت ها
emcache-1.0.0
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A high performance asynchronous Python client for Memcached with full batteries included
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | emcache-1.0.0 |
| نام | emcache |
| نسخه کتابخانه | 1.0.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Pau Freixes |
| ایمیل نویسنده | pfreixes@gmail.com |
| آدرس صفحه اصلی | http://github.com/emcache/emcache |
| آدرس اینترنتی | https://pypi.org/project/emcache/ |
| مجوز | - |
emcache
#######
A high performance asynchronous Python client for `Memcached <https://memcached.org/>`_ with full batteries included
.. image:: https://readthedocs.org/projects/emcache/badge/?version=latest
:target: https://emcache.readthedocs.io/en/latest/?badge=latest
.. image:: https://github.com/emcache/emcache/workflows/CI/badge.svg
:target: https://github.com/emcache/emcache/workflows/CI/badge.svg
.. image:: https://github.com/emcache/emcache/workflows/PyPi%20release/badge.svg
:target: https://github.com/emcache/emcache/workflows/PyPi%20release/badge.svg
Emcache stands on the giant's shoulders and implements most of the characteristics that are desired for a Memcached client based
on the experience of other Memcached clients, providing the following main characteristics:
- Support for many Memcached hosts, distributing traffic around them by using the `Rendezvous hashing <https://emcache.readthedocs.io/en/latest/advanced_topics.html#hashing-algorithm>`_ algorithm.
- Support for different commands and different flag behaviors like ``noreply``, ``exptime`` or ``flags``.
- Support for SSL/TLS protocol.
- Adaptative `connection pool <https://emcache.readthedocs.io/en/latest/advanced_topics.html#connection-pool>`_, which increases the number of connections per Memcache host depending on the traffic.
- `Node healthiness <https://emcache.readthedocs.io/en/latest/advanced_topics.html#healthy-and-unhealthy-nodes>`_ traceability and an optional flag for disabling unhealthy for participating in the commands.
- Metrics for `operations and connections <https://emcache.readthedocs.io/en/latest/cluster_managment.html#connection-pool-metrics>`_, send them to your favourite TS database for knowing how the Emcache driver is behaving.
- Listen to the most significant `cluster events <https://emcache.readthedocs.io/en/latest/advanced_topics.html#cluster-events>`_, for example for knowing when a node has been marked as unhealthy.
- Speed, Emcache is fast. See the benchmark section.
Usage
==========
For installing
.. code-block:: bash
pip install emcache
The following snippet shows the minimal stuff that would be needed for creating a new client and saving a new key and retrieving later the value.
.. code-block:: python
import asyncio
import emcache
async def main():
client = await emcache.create_client([emcache.MemcachedHostAddress('localhost', 11211)])
await client.set(b'key', b'value')
item = await client.get(b'key')
print(item.value)
await client.close()
asyncio.run(main())
Emcache has currently support, among many of them, for the following commands:
- **get** Used for retrieving a specific key.
- **gets** Cas version that returns also the case token of a specific key.
- **get_many** Many keys get version.
- **gets_many** Many keys + case token gets version.
- **set** Set a new key and value
- **add** Add a new key and value, if and only if it does not exist.
- **replace** Update a value of a key, if an only if the key does exist.
- **append** Append a value to the current one for a specific key, if and only if the key does exist.
- **prepend** Prepend a value to the current one for a specific key, if and only if the key does exist.
- **cas** Update a value for a key if and only if token as provided matches with the ones stored in the Memcached server.
Take a look at the documentation for getting a list of all of the `operations <https://emcache.readthedocs.io/en/latest/operations.html>`_ that are currently supported.
Some of the commands have support for the following behavior flags:
- ``noreply`` for storage commands like **set** we do not wait for an explicit response from the Memcached server. Sacrifice the explicit ack from the Memcached server for speed.
- ``flags`` for storage we can save an int16 value that can be retrieved later on by fetch commands.
- ``exptime`` for storage commands this provides a way of configuring an expiration time, once that time is reached keys will be automatically evicted by the Memcached server
For more information about usage, `read the docs <https://emcache.readthedocs.io/en/latest/>`_.
Benchmarks
===========
The following table shows how fast - operations per second - Emcache can be compared to the other two Memcached Python clients,
`aiomcache <https://github.com/aio-libs/aiomcache>`_ and `pymemcache <https://github.com/pinterest/pymemcache>`_.
For that specific benchmark two nodes were used, one for the client and one for the Memcached server, using 32 TCP connections
and using 32 concurrent Asyncio tasks - threads for the use case of Pymemcache. For Emcache and Aiomcache
`uvloop <https://github.com/MagicStack/uvloop>`_ was used as a default loop.
In the first part of the benchmark, the client tried to run as mucha **set** operations it could, and in a second step the same was
done but using **get** operations.
+------------------------+---------------+---------------+-------------------+--------------------+------------------+
| Client | Concurrency | Sets opS/sec | Sets latency AVG | Gets opS/sec | Gets latency AVG |
+========================+===============+===============+===================+====================+==================+
| aiomcache | 32 | 33872 | 0.00094 | 34183 | 0.00093 |
+------------------------+---------------+---------------+-------------------+--------------------+------------------+
| pymemcache | 32 | 32792 | 0.00097 | 32961 | 0.00096 |
+------------------------+---------------+---------------+-------------------+--------------------+------------------+
| emcache | 32 | 49410 | 0.00064 | 49212 | 0.00064 |
+------------------------+---------------+---------------+-------------------+--------------------+------------------+
| emcache (autobatching) | 32 | 49410 | 0.00064 | 89052 | 0.00035 |
+------------------------+---------------+---------------+-------------------+--------------------+------------------+
Emcache performed better than the other two implementations reaching almost 50K ops/sec for get and set operations. One autobatching is used
it can boost the throughtput x2 (more info about autobatching below)
Another benchmark was performed for comparing how each implementation will behave in case of having to deal with more than 1 node, a new
benchmark was performed with different cluster sizes but using the same methodology as the previous test by first, performing as many set
operations it could and later as many get operations it could. For this specific use test with Aiomemcahce could not be used since it
does not support multiple nodes.
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| Client | Concurrency | Memcahed Nodes| Sets opS/sec | Sets latency AVG | Gets opS/sec | Gets latency AVG |
+=============+=============+===============+===============+==================+==============+==================+
| pymemcache | 32 | 2 | 21260 | 0.00150 | 21583 | 0.00148 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| emcache | 32 | 2 | 42245 | 0.00075 | 48079 | 0.00066 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| pymemcache | 32 | 4 | 15334 | 0.00208 | 15458 | 0.00207 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| emcache | 32 | 4 | 39786 | 0.00080 | 47603 | 0.00067 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| pymemcache | 32 | 8 | 9903 | 0.00323 | 9970 | 0.00322 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
| emcache | 32 | 8 | 42167 | 0.00075 | 46472 | 0.00068 |
+-------------+-------------+---------------+---------------+------------------+--------------+------------------+
The addition of new nodes did not add almost degradation for Emcache, in the last test with 8 nodes Emcache reached 42K
get ops/sec and 46K set ops/sec. On the other hand, Pymemcached suffered substantial degradation making Emcache ~x5 times.
faster.
Autobatching
============
Autobatching provides you a way for fetching multiple keys using a single command, batching happens transparently behind the scenes
without bothering the caller.
For start using the autobatching feature you must provide the parameter `autobatching` as True, hereby all usages of the `get` and `gets`
command will send batched requests behind the scenes.
Get´s are piled up until the next loop iteration. Once the next loop iteration is reached all get´s are transmitted using the
same Memcached operation.
Autobatching can boost up the throughput of your application x2/x3.
Development
===========
Clone the repository and its murmur3 submodule
.. code-block:: bash
git clone --recursive git@github.com:emcache/emcache
Compile murmur3
.. code-block:: bash
pushd vendor/murmur3
make static
popd
Install emcache with dev dependencies
.. code-block:: bash
make install-dev
نیازمندی
| مقدار | نام |
|---|---|
| ==0.29.32 | Cython |
| ==6.2.5 | pytest |
| ==3.1.0 | pytest-mock |
| ==0.11.0 | pytest-asyncio |
| ==2.8.1 | pytest-cov |
| ==22.3.0 | black |
| ==4.3.21 | isort |
| ==3.7.9 | flake8 |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.8 | Python |
نحوه نصب
نصب پکیج whl emcache-1.0.0:
pip install emcache-1.0.0.whl
نصب پکیج tar.gz emcache-1.0.0:
pip install emcache-1.0.0.tar.gz