serpy | ridiculously fast object serialization
kandi X-RAY | serpy Summary
kandi X-RAY | serpy Summary
ridiculously fast object serialization
Top functions reviewed by kandi - BETA
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of serpy
serpy Key Features
serpy Examples and Code Snippets
Community Discussions
Trending Discussions on serpy
QUESTION
ANSWER
Answered 2019-Jan-12 at 15:38Serpy has the .to_value
method that can be overridden to perform custom serialization akin to DRFs .to_representation
.
You'll likely want to call the base class first within your .to_value
method.
QUESTION
I'm developing a GeoDjango app which use the provided WorldBorder model in the tutorial. I also created my own Region model which is tied to WorldBorder. So a WorldBorder/Country can have multiple Regions which has borders (MultiPolygon field) in it too.
I made the API for it using DRF but it's so slow, it takes 16 seconds to load all WorldBorder and Regions in GeoJSON format. The returned JSON size is 10MB though. Is that reasonable?
I even change the serializer to serpy which is way much faster than the DRF GIS serializer but only offers 10% performance improvement.
Turns out after profiling, most of the time is spent in the GIS functions to convert data type in the database to list of coordinates instead of WKT. If I use WKT, the serialization is much faster (1.7s compared to 11.7s, the WKT is only for WorldBorder MultiPolygon, everything else is still in GeoJson)
I also tried to compress the MultiPolygon using ST_SimplifyVW with low tolerance (0.005) to preserve the accuracies, which brings down the JSON size to 1.7 MB. This makes the total load to 3.5s. Of course I can still find which is the best tolerance to balance accuracy and speed.
Below is the profiling data (the sudden increase of queries in the simplified MultiPolygon is due to bad usage of Django QS API to get use of ST_SimplifyVW)
EDIT: I fixed the DB query so the query calls stays the same at 75 queries and as expected, it does not increase the performance significantly.
EDIT: I continued to improve my DB queries. I reduced it to just 8 queries now. As expected, it does not improve that much performance.
Below is profiling for the function calls. I highlight the part which took most of the time. This one is using vanilla DRF GIS implementation.
Below is when I use WKT for one of the MultiPolygon field without ST_SimplifyVW.
Here's the models as requested by @Udi
...ANSWER
Answered 2018-Jan-01 at 20:08Since your geographic data does not change frequently, try caching all region/country polygons in pre-calculated geojsons. I.e., create a /country/123.geojson
API call or static file with the geo data for all regions in this country, probably simplified in advance.
Your other API calls should return only the numeric data, without geographic polygons, leaving the combining task to the client.
QUESTION
I have a CSV on the hadoop file system hdfs that I want to convert into multiple serialized java objects using this framework:
...ANSWER
Answered 2017-Dec-14 at 15:57The output objects should be readable by a normal non-hadoop/spark related Java program
For that to work you will need to save your results outside of HDFS. So what you could do is:
- Read the CSV data from HDFS using SparkContext.textFile in Spark
- Grab a limited number of rows into your driver using RDD.take()
- The argument here will be the number of rows you want e.g. myRdd.take(1000) to grab 1000 rows
- myRdd.collect() will grab everything, but if you have a lot of data, that can cause an OutOfMemoryError on your spark driver
- Now you will have all the rows as an array, you can store them using a basic java serializer
Sample Code:
QUESTION
Using python 3.5.2 and django 1.11 multitable inheritance like this:
...ANSWER
Answered 2017-Jul-02 at 20:48This has nothing to do with the manager, or indeed with Django at all. A list comprehension always constructs a list; that is its main purpose. But the only thing you're doing inside that list comp is calling print()
, which returns None. So the result of that entire expression is a list containing a single None, which the shell helpfully prints for you.
Really, you should not use list comprehensions for their side effects. Use a proper loop.
QUESTION
Given two different models, with the same parent base class. Is there any way, using either Django Rest Framework Serializers or serpy, to serialize a chained list containing instances of both the child models?
Given some example models:
...ANSWER
Answered 2017-Jan-19 at 14:45From your exception I suppose problem with a BaseModelSerializer
because it have both fields from both models. I think your better write a two separate serializers for each models and then sort output from them by common field:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install serpy
No Installation instructions are available at this moment for serpy.Refer to component home page for details.
Support
If you have any questions vist the community on GitHub, Stack Overflow.
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page