This document discusses principles for writing readable Python code, including locality, consistency, and verbosity. It emphasizes that code should be written to be easily understood rather than clever, with related elements kept together, common patterns used consistently, and explanations provided through comments when the code is not obvious. The goal is for code to fit easily in the reader's head so it can be maintained and built upon over time by others, including the original author.
Using Buildout to Develop and Deploy Python ProjectsClayton Parker
Buildout gives you a way to manage, build and deploy your Python project with ease. Large Python projects such as Plone use it to distribute repeatable development environments. Buildout allows you to easily get up and running with your project versus the traditional method of installing all the dependancies and manually configuring your applications instance for each environment. The buildout community is rapidly growing with a large repository of recipes that allow you to extend it's functionality. This talk will show you the basics of using buildout and how to make it a vital part of your project's life cycle.
2013 Tips and Tricks Mashup, From ModelBuilder to Formal Python Code, Step-by...GIS in the Rockies
ArcGIS ModelBuilder provides the user with a simple way to capture geoprocessing instructions as a Python script. This presentation explores the path to promote that script into formal production level code. Beginning with the geoprocessing foundation exported from ModelBuilder, we augment the code to:
• clarify the command line parameters
• organize the directories
• set the SDE workspace
• insert print commands
• check if feature classes exist
• use try / catch blocks to trap errors
• execute operating system commands
• add logging throughout the code
The end result of these additions is production level code that is easy to maintain and deploy. It is particularly well-suited to run automatically as a Windows Scheduled Task.
This session is intended for users who are getting started with Python, or even just thinking about it.
Using Buildout to Develop and Deploy Python ProjectsClayton Parker
Buildout gives you a way to manage, build and deploy your Python project with ease. Large Python projects such as Plone use it to distribute repeatable development environments. Buildout allows you to easily get up and running with your project versus the traditional method of installing all the dependancies and manually configuring your applications instance for each environment. The buildout community is rapidly growing with a large repository of recipes that allow you to extend it's functionality. This talk will show you the basics of using buildout and how to make it a vital part of your project's life cycle.
2013 Tips and Tricks Mashup, From ModelBuilder to Formal Python Code, Step-by...GIS in the Rockies
ArcGIS ModelBuilder provides the user with a simple way to capture geoprocessing instructions as a Python script. This presentation explores the path to promote that script into formal production level code. Beginning with the geoprocessing foundation exported from ModelBuilder, we augment the code to:
• clarify the command line parameters
• organize the directories
• set the SDE workspace
• insert print commands
• check if feature classes exist
• use try / catch blocks to trap errors
• execute operating system commands
• add logging throughout the code
The end result of these additions is production level code that is easy to maintain and deploy. It is particularly well-suited to run automatically as a Windows Scheduled Task.
This session is intended for users who are getting started with Python, or even just thinking about it.
In this talk we will explore the Zen of Python and the famous PEP8 Style Guide. Learn about the tenets of the Python language and how you can apply them to make your code beautiful and functional. After all, Readability Counts!
MongoDB is a popular NoSQL database. This presentation was delivered during a workshop.
First it talks about NoSQL databases, shift in their design paradigm, focuses a little more on document based NoSQL databases and tries drawing some parallel from SQL databases.
Second part, is for hands-on session of MongoDB using mongo shell. But the slides help very less.
At last it touches advance topics like data replication for disaster recovery and handling big data using map-reduce as well as Sharding.
You can't spell "monitoring" without "monoid"kscaldef
Well, technically you can, but if you do you’re probably lying to yourself with the data you’re collecting.
If you care about aggregating your monitoring data over time or across dimensions like hosts or container instances, you care about monoids; you just might not know it! In this talk, I’ll explain what a monoid is (it’s not scary, I promise!) and why they form the basis for scalable telemetry data types. We’ll see how naive approaches to metrics can end up giving you the wrong answers to important questions and how a more mathematically well-founded approach can fix those problems.
Tips And Tricks For Bioinformatics Software Engineeringjtdudley
This is a talk I've given twice at Stanford recently. It's essentially a brain dump of my thoughts on being a Bioinformatician with lots of links to useful tools.
Data Science. .Net/C# Monte Carlo modeling. The R Programming language. See it all come together in one place in this talk. Presentation date 6/13 at Lake County .NET User Group.
PyDX Presentation about Python, GeoData and MapsHannes Hapke
This presentation introduces you to the basics of geospatial data and guides you through two examples for Django. First, you will learn how to program a small GeoDjango project. And secondly, you will learn how to extend the project with a few lines of code to turn the Django project into an API endpoint, which can be consumed by your mobile clients or java script single page applications.
Beyond Breakpoints: A Tour of Dynamic AnalysisC4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2dXUUTG.
Nathan Taylor provides an introduction to the dynamic analysis research space, suggesting integrating these techniques into various internal tools. Filmed at qconnewyork.com.
Nathan Taylor is a software developer currently employed at Fastly, where he works on making the Web faster through high performance content delivery. Previous gigs have included hacking on low-level systems software such as Java runtimes at Twitter and, prior to that, the Xen virtual machine monitor in grad school.
Screencasting and Presenting for EngineersKunal Johar
Engineers often think about the 'how' as the most exciting part of their work. These details often bore what would be candid listeners.
Take a step back, think about what excites others, then ease in your grand challenges. Tie it all together in a story.
In this talk we will explore the Zen of Python and the famous PEP8 Style Guide. Learn about the tenets of the Python language and how you can apply them to make your code beautiful and functional. After all, Readability Counts!
MongoDB is a popular NoSQL database. This presentation was delivered during a workshop.
First it talks about NoSQL databases, shift in their design paradigm, focuses a little more on document based NoSQL databases and tries drawing some parallel from SQL databases.
Second part, is for hands-on session of MongoDB using mongo shell. But the slides help very less.
At last it touches advance topics like data replication for disaster recovery and handling big data using map-reduce as well as Sharding.
You can't spell "monitoring" without "monoid"kscaldef
Well, technically you can, but if you do you’re probably lying to yourself with the data you’re collecting.
If you care about aggregating your monitoring data over time or across dimensions like hosts or container instances, you care about monoids; you just might not know it! In this talk, I’ll explain what a monoid is (it’s not scary, I promise!) and why they form the basis for scalable telemetry data types. We’ll see how naive approaches to metrics can end up giving you the wrong answers to important questions and how a more mathematically well-founded approach can fix those problems.
Tips And Tricks For Bioinformatics Software Engineeringjtdudley
This is a talk I've given twice at Stanford recently. It's essentially a brain dump of my thoughts on being a Bioinformatician with lots of links to useful tools.
Data Science. .Net/C# Monte Carlo modeling. The R Programming language. See it all come together in one place in this talk. Presentation date 6/13 at Lake County .NET User Group.
PyDX Presentation about Python, GeoData and MapsHannes Hapke
This presentation introduces you to the basics of geospatial data and guides you through two examples for Django. First, you will learn how to program a small GeoDjango project. And secondly, you will learn how to extend the project with a few lines of code to turn the Django project into an API endpoint, which can be consumed by your mobile clients or java script single page applications.
Beyond Breakpoints: A Tour of Dynamic AnalysisC4Media
Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2dXUUTG.
Nathan Taylor provides an introduction to the dynamic analysis research space, suggesting integrating these techniques into various internal tools. Filmed at qconnewyork.com.
Nathan Taylor is a software developer currently employed at Fastly, where he works on making the Web faster through high performance content delivery. Previous gigs have included hacking on low-level systems software such as Java runtimes at Twitter and, prior to that, the Xen virtual machine monitor in grad school.
Screencasting and Presenting for EngineersKunal Johar
Engineers often think about the 'how' as the most exciting part of their work. These details often bore what would be candid listeners.
Take a step back, think about what excites others, then ease in your grand challenges. Tie it all together in a story.
As a data science Intern at Leapcheck Services private limited, I have developed a naive chatbot using sequence to sequence model by LSTM of RNN. Sharing the tutorial which I made explicitly for the deep learning enthusiasts to
provide them a basic insight on how chatbot can be developed with the help of recurrent neural network.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
17. “There's a difference between
getting your hands dirty and
being dirty.”
DS Justin Ripley
(yes, the picture is not
from Luther, but from
The Good Cop)
40. Related classes on
the same module
Keep files short
Function used only in
a module not in
independent module
Avoid
boilerplate
Separated
business logic
51. results = []
for row in query_results:
tag, value, updated = row
if value and updated > last_time:
TEMP = ‘tag: {0}, value: {1}
result = TEMP.format(tag,
value)
results.append(result)
52. def format_result(row):
tag, value, _ = row
TEMP = ‘tag: {0}, value: {1}’
return TEMP.format(tag, value)
def interesting(row):
_, value, updated = row
return value and updated > last_time
results = [format_result(row)
for row in query_results
if interesting(row)]