#PYTHON
Exploring Mountain Huts with SPARQL and Wikidata
Utilize SPARQL and Wikidata to efficiently query and retrieve data on mountain huts based on specified latitude and longitude coordinates.
#python
BlueYonder at PyCon.DE 2023
It's been now 10 years ago when Blue Yonder started the first sponsoring of a python
conference at Europython Florence. Since then we have been either sponsoring
and/or organizing at least one python event per year.
#python
#conference
beautiful leaflet markers with folium and fontawesome
TIL how to use fontawesome markers with folium.
#python
#pydata
#visualization
#til
scaling-aware rating of count forecasts
Forecasts crave a rating that reflects the forecast's quality in the context
of what is possible in theory and what is reasonable to expect in practice.
#pydata
#python
#meetup
Python Support in Snowflake
Snowflake offers different ways to access and call python from within their
compute infrastructure. This post will show how to access python in
user defined functions, via stored procedures and in snowpark.
#python
#sql
#snowflake
#pydata
Convert the Himalayan Database to SQLite
Conversion of the Himalayan database of the legendary Elizabeth Hawley from FoxPro to SQLite.
#python
#sql
#mountain
Azure Synapse SQL-on-Demand Openrowset Common Table Expression with SQLAlchemy
Using SQLAlchemy to create openrowset common table expressions for Azure Synapse SQL-on-Demand
#python
#sql
#pydata
#azure
Using turbodbc to access Azure Synapse SQL-on-Demand endpoints
Azure Synapse SQL-on-Demand offers a web client, the desktop version
Azure Data studio and odbc access with turbodbc to query parquet files in
the Azure Data Lake.
#python
#sql
#pydata
#azure
Azure Data Explorer and Parquet files in the Azure Blob Storage
Last summer Microsoft has rebranded the Azure Kusto Query engine as Azure Data Explorer. While it does not support fully elastic scaling, it at least allows to scale up and out a cluster via an API or the Azure portal to adapt to different workloads. It also offers parquet support out of the box which made me spend some time to look into it.
#python
#pydata
#azure
#parquet
Understand predicate pushdown on row group level in Parquet with pyarrow and python
Apache Parquet is a columnar file format to
work with gigabytes of data. Reading and writing parquet files is efficiently
exposed to python with pyarrow. Additional statistics allow clients to use
predicate pushdown to only read subsets of data to reduce I/O.
Organizing data by column allows for better
compression, as data is more homogeneous. Better compression also reduces the
bandwidth required to read the input.
#python
#pydata
#parquet
#arrow
#pandas
Azure Data Lake Storage Gen 2 with Python
Microsoft has released a beta version of the python client azure-storage-file-datalake for the Azure Data Lake Storage Gen 2 service with support for hierarchical namespaces.
#python
#pydata
Karlsruhe Python Meetup at Blue Yonder
Python Meetup with two talks about python usage in a data science environment
and the different stages of a python package in this environment.
#python
#meetup
#conference
JDA ICON - Enabler of AI - Overview of an AI Architecture
JDA ICON 2019 was all about technology, APIs, AI (Artificial Intelligence)
and ML (Machine Learning).
#python
#talk
PyCon.DE 2018
PyCon.DE 2018 is over. Second time in a row we organized it in ZKM Karlsruhe.
Next year PyCon.DE will move to Berlin.
#python
#conference
EuroSciPy 2018 - Apache Parquet as a columnar storage for large datasets
Apache Parquet is an binary, efficient columnar data format that can be used for high performance data I/O in Pandas and Dask.
#python
#talk
Europython 2018 - Using Pandas and Dask to work with large columnar datasets in Apache Parquet
Apache Parquet is an binary, efficient columnar data format that can be used for high performance data I/O in Pandas and Dask.
#python
#talk
Swiss Python Summit 2018 - 12 Factor Apps for Data-Science with Python
Heroku distilled their principles to build modern cloud applications. These principles have influenced many of our design decisions at Blue Yonder to build a data science platform.
#python
#talk
How to organize a PyCon.DE
Some notes on how to organize a conference like PyCon.DE
#python
#conference
PyCon.DE 2017 and PyData Karlsruhe
The venue setup @zkmkarlsruhe for #PyCon.DE 2017 and PyData Karlsruhe is done.
We are ready for liftoff tomorrow.
#python
EuroPython 2017 - Infrastructure as Python Code, Run your Services on Microsoft Azure
Using Infrastructure-as-Code principles with configuration through machine processable definition files in combination with the adoption of cloud computing provides faster feedback cycles in development/testing and less risk in deployment to production.
#python
#talk
PyConWeb 2017 Munich - Deploying your Web Services on Microsoft Azure
This talk will give an overview on how to deploy web services on the Azure Cloud with different tools like Azure Resource Manager Templates, the Azure SDK for Python and the Azure module for Ansible and present best practices learned while moving a company into the Azure Cloud.
#python
#talk
PyCon.DE 25-27th October 2017 Karlsruhe
The next PyCon.DE will be from 25-27th October 2017 at the ZKM - center for
art and media in Karlsruhe/Germany.
#python
#conference
Getting started with the Cloudera Kudu storage engine in python
Cloudera Kudu is a distributed storage engine for fast data analytics.
The python api is in alpha stage but already usable.
#python
#pydata
#spark
PyScaffold - Easy setup of a Python project with a bliss
PyScaffold helps you to easily setup a new Python project.
#python
EuroPython 2015 PySpark - Data Processing in Python on top of Apache Spark
Apache Spark is a computational engine for large-scale data processing.
PySpark exposes the Spark programming model to Python. It defines an API
for Resilient Distributed Datasets (RDDs) and the DataFrame API.
#python
#pydata
#spark
#talk
PyData 2015 Berlin - Introduction to the PySpark DataFrame API
This Talk from PyData 2015 Berlin gives an overview of the PySpark Data Frame API.
#python
#pydata
#spark
#talk
Structured Logging with Python and CEE Syslog Handler
cee_syslog_handler is an extension to the python syslog logging handler with support for structured json messages.
#python
EuroPython 2014 - Log everything with Logstash and Elasticsearch
When your application grows beyond one machine you need a central space to
log, monitor and analyze what is going on. Logstash and elasticsearch store
your logs in a structured way. Kibana is a web fronted to search and
aggregate your logs.
#python
#elasticsearch
#talk
Go for Python Hackers
There is a resurgence of native-compiled programming languages going on.
Some of this work is in response to Python; we're now part of The
Establishment against which newcomers are measured. Greg Ward gives an overview
of Go, a recent native-compiled language, and how it relates to Python.
#python
PyCon Russia - Redis Talk
Amir Salihefendic talks about Redis, scaling plurk.com and some python
libraries on top of redis like bitmapist.
#python
#nosql
Simple Twitter Streaming API access with Python and Oauth
Python example to access the twitter API on your behalf, without going
through three legged autorization.
#python