#PYTHON
Utilize SPARQL and Wikidata to efficiently query and retrieve data on mountain huts based on specified latitude and longitude coordinates. Read More
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. Read More
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. Read More
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. Read More
Conversion of the Himalayan database of the legendary Elizabeth Hawley from FoxPro to SQLite. Read More
Using SQLAlchemy to create openrowset common table expressions for Azure Synapse SQL-on-Demand Read More
Inspired by Uwe Korns post on DuckDB this post shows how to use Azure Synapse SQL-on-Demand to query parquet files with T-SQL on a serverless cloud infrastructure. Read More
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. Read More
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. Read More
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. Read More
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. Read More
Python Meetup with two talks about python usage in a data science environment and the different stages of a python package in this environment. Read More
JDA ICON 2019 was all about technology, APIs, AI (Artificial Intelligence) and ML (Machine Learning). Read More
PyCon.DE 2018 is over. Second time in a row we organized it in ZKM Karlsruhe. Next year PyCon.DE will move to Berlin. Read More
Apache Parquet is an binary, efficient columnar data format that can be used for high performance data I/O in Pandas and Dask. Read More
Apache Parquet is an binary, efficient columnar data format that can be used for high performance data I/O in Pandas and Dask. Read More
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. Read More
The venue setup @zkmkarlsruhe for #PyCon.DE 2017 and PyData Karlsruhe is done. We are ready for liftoff tomorrow. Read More
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. Read More
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. Read More
The next PyCon.DE will be from 25-27th October 2017 at the ZKM - center for art and media in Karlsruhe/Germany. Read More
Cloudera Kudu is a distributed storage engine for fast data analytics. The python api is in alpha stage but already usable. Read More
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. Read More
This Talk from PyData 2015 Berlin gives an overview of the PySpark Data Frame API. Read More
cee_syslog_handler is an extension to the python syslog logging handler with support for structured json messages. Read More
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. Read More
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. Read More
Amir Salihefendic talks about Redis, scaling plurk.com and some python libraries on top of redis like bitmapist. Read More
Python example to access the twitter API on your behalf, without going through three legged autorization. Read More