Python is an open source scripting language that can be used independently or within ArcGIS to automate geoprocessing and map creation tasks. It allows users to easily share and expand geoprocessing tools. Python code can be written in various integrated development environments (IDEs) or text editors and then run to create and automate workflows, extend existing tools with custom logic, write new tools, and access other modules to analyze geospatial data. Online training resources are available to help users learn Python scripting.
This document provides an overview of a Python Programming for ArcGIS workshop, including:
- The workshop will teach Python skills to access ArcGIS commands, attribute tables, and geometries for geoprocessing.
- An outline of topics includes introductions to Python and ArcGIS, programming principles and modules, ModelBuilder, and reading and writing data.
- Examples of Python code are provided to demonstrate basic concepts like variables, conditionals, loops, importing modules, and file manipulation.
This document discusses how automation can be used with geodatabases in ArcGIS using the ArcPy module in Python. It provides examples of using ArcPy to explore geodatabase content, simplify administrative tasks like creating indexes and setting privileges, and implement data workflows like conversion and distribution. ArcPy allows access to common data structures, geoprocessing tools, and map documents through its modules. Understanding geodatabases, Python concepts, and the ArcPy package are required to automate tasks with the geodatabase.
This document provides a summary of a presentation on Python for Everyone. The presentation outline includes an introduction, overview of what Python is, why use Python, where it fits in, and how to automate workflows using Python for both desktop and server applications in ArcGIS. It also discusses ArcGIS integration with Python using ArcPy and resources for learning more about Python. The presentation includes demonstrations of automating tasks using Python for desktop and server applications. It promotes official Esri training courses on Python and provides resources for learning more about Python for GIS tasks.
Leveraging Open Source GIS with Python: A QGIS ApproachGerry James
The accompanying slide presentation to a webinar I gave back in may showing the power of Python with open source tools like Quantum GIS (QGIS) and PostGIS.
Pulumi is an open source infrastructure as code tool that allows developers to define cloud infrastructure in popular programming languages like TypeScript, Python, and Go. This enables infrastructure to be defined as code and deployed consistently across clouds like AWS, Azure, and GCP. Pulumi uses a desired state model where it compares the actual and desired state of resources and only makes changes where needed. It was created by a Seattle startup in 2018 and supports defining infrastructure from code for both traditional resources like VMs as well as modern architectures like containers and serverless functions.
This document provides an outline on learning the Go programming language. It discusses Go's history as a language developed by Google in 2007. Key features include being statically typed with garbage collection and support for concurrency. The document outlines disadvantages like Go still being a young language. It provides guidance on setting up a Go environment and learning basics like types, variables, functions, control structures, object orientation, and concurrency using goroutines and channels.
Infrastructure-as-Code with Pulumi- Better than all the others (like Ansible)?Jonas Hecht
There's a new Infrastructure-as-Code (IaC) kid on the block: Pulumi is there to frighten the established: Chef, Puppet, Terraform, Cloudformation, Ansible... But is it really the "better" tool and how could they be compared? Is it only hype-driven? We'll find out, incl. lot's of example code. (ContainerConf / Continuous Lifecycle 2019 Talk in Mannheim)
Example GitHub code: https://github.com/jonashackt/pulumi-python-aws-ansible
https://github.com/jonashackt/pulumi-typescript-aws-fargate
Python is an open source scripting language that can be used independently or within ArcGIS to automate geoprocessing and map creation tasks. It allows users to easily share and expand geoprocessing tools. Python code can be written in various integrated development environments (IDEs) or text editors and then run to create and automate workflows, extend existing tools with custom logic, write new tools, and access other modules to analyze geospatial data. Online training resources are available to help users learn Python scripting.
This document provides an overview of a Python Programming for ArcGIS workshop, including:
- The workshop will teach Python skills to access ArcGIS commands, attribute tables, and geometries for geoprocessing.
- An outline of topics includes introductions to Python and ArcGIS, programming principles and modules, ModelBuilder, and reading and writing data.
- Examples of Python code are provided to demonstrate basic concepts like variables, conditionals, loops, importing modules, and file manipulation.
This document discusses how automation can be used with geodatabases in ArcGIS using the ArcPy module in Python. It provides examples of using ArcPy to explore geodatabase content, simplify administrative tasks like creating indexes and setting privileges, and implement data workflows like conversion and distribution. ArcPy allows access to common data structures, geoprocessing tools, and map documents through its modules. Understanding geodatabases, Python concepts, and the ArcPy package are required to automate tasks with the geodatabase.
This document provides a summary of a presentation on Python for Everyone. The presentation outline includes an introduction, overview of what Python is, why use Python, where it fits in, and how to automate workflows using Python for both desktop and server applications in ArcGIS. It also discusses ArcGIS integration with Python using ArcPy and resources for learning more about Python. The presentation includes demonstrations of automating tasks using Python for desktop and server applications. It promotes official Esri training courses on Python and provides resources for learning more about Python for GIS tasks.
Leveraging Open Source GIS with Python: A QGIS ApproachGerry James
The accompanying slide presentation to a webinar I gave back in may showing the power of Python with open source tools like Quantum GIS (QGIS) and PostGIS.
Pulumi is an open source infrastructure as code tool that allows developers to define cloud infrastructure in popular programming languages like TypeScript, Python, and Go. This enables infrastructure to be defined as code and deployed consistently across clouds like AWS, Azure, and GCP. Pulumi uses a desired state model where it compares the actual and desired state of resources and only makes changes where needed. It was created by a Seattle startup in 2018 and supports defining infrastructure from code for both traditional resources like VMs as well as modern architectures like containers and serverless functions.
This document provides an outline on learning the Go programming language. It discusses Go's history as a language developed by Google in 2007. Key features include being statically typed with garbage collection and support for concurrency. The document outlines disadvantages like Go still being a young language. It provides guidance on setting up a Go environment and learning basics like types, variables, functions, control structures, object orientation, and concurrency using goroutines and channels.
Infrastructure-as-Code with Pulumi- Better than all the others (like Ansible)?Jonas Hecht
There's a new Infrastructure-as-Code (IaC) kid on the block: Pulumi is there to frighten the established: Chef, Puppet, Terraform, Cloudformation, Ansible... But is it really the "better" tool and how could they be compared? Is it only hype-driven? We'll find out, incl. lot's of example code. (ContainerConf / Continuous Lifecycle 2019 Talk in Mannheim)
Example GitHub code: https://github.com/jonashackt/pulumi-python-aws-ansible
https://github.com/jonashackt/pulumi-typescript-aws-fargate
GoLang is an open source programming language created by Google in 2009. It has a large community and was designed for scalability and concurrency. Some key features include being statically typed, compiled, and having built-in support for concurrency through goroutines and channels. Google uses GoLang extensively to build systems that scale to thousands of machines.
This document provides an overview of Pulumi, an infrastructure as code platform. It discusses what Pulumi is, the programming languages supported like TypeScript, JavaScript, Python, Go and .NET, and the cloud providers supported like AWS, Azure, GCP etc. It also provides a comparison of Pulumi with other infrastructure as code tools like Terraform, CloudFormation and ARM templates in terms of factors like supported languages, state management, stack management etc. Finally, it outlines the steps to get started with Pulumi including installing it, logging into Azure and creating a new Pulumi project.
This document provides an overview of C and C++, including:
- Five reasons to learn C/C++, such as industry usage and useful for other modules.
- The history of C and C++, from the creation of C at Bell Labs in the 1970s to the development of C++ in the 1980s.
- The aims of C, such as ability to write low-level code and efficiency, versus the aims of C++ which grew from C while keeping some similar aims.
- The differences between procedural and object-oriented languages, and how C++ allows both paradigms while C is purely procedural.
- The similarities and differences between C and C++ in
This document provides an introduction to Python programming basics for beginners. It discusses Python features like being easy to learn and cross-platform. It covers basic Python concepts like variables, data types, operators, conditional statements, loops, functions, OOPs, strings and built-in data structures like lists, tuples, and dictionaries. The document provides examples of using these concepts and recommends Python tutorials, third-party libraries, and gives homework assignments on using functions like range and generators.
Go is an open source programming language designed by Google to be concurrent, garbage collected, and efficient. It has a simple syntax and is used by Google and others to build large distributed systems. Key features include garbage collection, concurrency with goroutines and channels, interfaces without inheritance, and a large standard library.
Go is a new systems programming language from Google. Go has many interesting features such as 'communication channels' that makes it suitable for use in multi-core machines, and network programming. With Ken Thompson (of Unix fame) as one of its designers, Go has elegant and minimal design that is appealing to most programmers. This talk gives a technical introduction to Go that is of interest to anyone working in system software.
[Presentation I have in 2010 - I haven't updated it with recent changes to the Go language]
GoLang is an open source programming language created by Google in 2009. It has a large community and was designed for scalability and concurrency. Some key features include being statically typed, compiled, and having built-in support for concurrency through goroutines and channels. Google uses GoLang extensively to build systems that scale to thousands of machines.
Esri International User Conference 2011: Python: Integrating Standard and Thi...jasonscheirer
This document summarizes a technical workshop on integrating standard and third-party Python libraries for use in ArcGIS. It discusses leveraging built-in Python libraries for common tasks like file I/O, networking, and data structures. It also covers finding and installing third-party libraries from the Python Package Index and providing examples of libraries for tasks like PDF generation, image processing, and Excel integration. The document emphasizes exploring Python's documentation and reusing existing libraries rather than reimplementing functionality.
Dart is an open-source programming language created by Google that compiles to JavaScript and allows developers to build web and server applications with a single language. Dart is easy to learn and comes with features like classes, interfaces, optional static types, lexical scoping, libraries, and isolates. It also includes a lightweight editor. A basic Dart program defines a printNumber function that prints a number, declares and initializes a variable, and calls the function to print the number. Dart code execution is supported in the browser via JavaScript compilation and on the server. The Dart team includes Lars Bak and Gilad Bracha who have experience with Java, JavaScript, and software patents.
This document outlines an agenda for a session on the Go programming language. It covers Go's history and development, grammar and syntax, concurrency features using CSP, the standard library and toolchain, interfacing Go with C, popular production and open source projects using Go, and reference materials. The session aims to provide an overview of Go's key features and how it is used in practice.
This document outlines the steps to train a custom object detection model using TensorFlow and Google Cloud Platform. It includes setting up prerequisites like TensorFlow and Google Cloud SDK, creating training datasets with images and annotations, converting data to TFRecord format, training a model using transfer learning on Cloud ML Engine, exporting the trained model, and testing the model.
SciPipe - A light-weight workflow library inspired by flow-based programmingSamuel Lampa
A presentation of the SciPipe workflow library, written in Go (Golang), inspired by Flow-based programming, at an internal workshop at Uppsala University, Department of Pharmaceutical Biosciences.
Using Aspects for Language Portability (SCAM 2010)lennartkats
This document discusses using aspects for language portability. It introduces four classes of portability aspects: 1) glue code aspects, 2) migration aspects, 3) integration aspects, and 4) optimization aspects. These aspects address additional portability issues beyond just replacing the backend, such as platform-specific libraries, unportable code, platform integration, and performance. Aspect-oriented programming is proposed as an elegant way to encapsulate platform-specific concerns in separate libraries.
Object oriented programming 7 first steps in oop using c++Vaibhav Khanna
Advantages of C++
Portability. C++ offers the feature of portability or platform independence which allows the user to run the same program on different operating systems or interfaces at ease. ...
Object-oriented. ...
Multi-paradigm. ...
Low-level Manipulation. ...
Memory Management. ...
Large Community Support. ...
Compatibility with C. ...
Scalability.
This document discusses the use of Python for geospatial applications. It describes Python as a programming language designed for beginners that has been integrated into ArcGIS and matured in ArcGIS 10. It provides examples of how Python is used with ArcGIS for tasks like standardizing school boundary data, analyzing wildlife photos, and creating spatial data packages. The conclusion encourages the use of Python for working with data and notes how the ArcPy library has matured for fast data access and useful Python toolboxes.
This document provides an overview of machine learning in Python using key Python libraries. It discusses popular Python libraries for machine learning like NumPy, SciPy, Pandas, Matplotlib and scikit-learn. It outlines the typical steps in a machine learning project including defining the problem, preparing and summarizing data, evaluating algorithms, and presenting results. It also introduces the Iris dataset as a sample classification dataset and discusses loading, handling and visualizing sample data for a machine learning project in Python.
When working with big data or complex algorithms, we often look to parallelize our code to optimize runtime. By taking advantage of a GPUs 1000+ cores, a data scientist can quickly scale out solutions inexpensively and sometime more quickly than using traditional CPU cluster computing. In this webinar, we will present ways to incorporate GPU computing to complete computationally intensive tasks in both Python and R.
See the full presentation here: 👉 https://vimeo.com/153290051
Learn more about the Domino data science platform: https://www.dominodatalab.com
This document discusses scaling R to large datasets using Scala and Akka. It describes how R has limitations for parallelism and handling large data in memory. The author demonstrates reading a large CSV file of 100 million doubles (1.7GB) in parallel using Scala, Akka actors and Rserve. Producer and Worker actors divide the file and sum parts in Rserve. This allows scaling R computations to large data beyond a single machine's memory. Potential applications mentioned include optimization, distributed linear algebra, machine learning and statistics.
This document provides an overview of ESRI and ArcGIS. It discusses that ESRI was founded in 1969 and began developing GIS tools in the 1980s, releasing their first commercial software ARC/INFO in 1982. It then summarizes the history of ArcGIS, including the releases of ArcView in the 1990s, ArcGIS 8.X in 1999, and ArcGIS 9.X in 2004. The document also outlines the different ArcGIS Desktop components and levels, as well as the industries where ArcGIS is applicable, such as agriculture, utilities, government, and more.
This document provides an overview of editing features in ArcGIS 10X. It discusses the changes to the editing interface and tools compared to previous versions. Key changes include the introduction of feature templates to define how features are constructed and attributed. It also covers the new Create Features window that combines the target layer and sketch tools. The document reviews the various feature construction tools available through the templates, toolbars, and editor menu. It provides details on how to edit existing feature vertices and sketches.
GoLang is an open source programming language created by Google in 2009. It has a large community and was designed for scalability and concurrency. Some key features include being statically typed, compiled, and having built-in support for concurrency through goroutines and channels. Google uses GoLang extensively to build systems that scale to thousands of machines.
This document provides an overview of Pulumi, an infrastructure as code platform. It discusses what Pulumi is, the programming languages supported like TypeScript, JavaScript, Python, Go and .NET, and the cloud providers supported like AWS, Azure, GCP etc. It also provides a comparison of Pulumi with other infrastructure as code tools like Terraform, CloudFormation and ARM templates in terms of factors like supported languages, state management, stack management etc. Finally, it outlines the steps to get started with Pulumi including installing it, logging into Azure and creating a new Pulumi project.
This document provides an overview of C and C++, including:
- Five reasons to learn C/C++, such as industry usage and useful for other modules.
- The history of C and C++, from the creation of C at Bell Labs in the 1970s to the development of C++ in the 1980s.
- The aims of C, such as ability to write low-level code and efficiency, versus the aims of C++ which grew from C while keeping some similar aims.
- The differences between procedural and object-oriented languages, and how C++ allows both paradigms while C is purely procedural.
- The similarities and differences between C and C++ in
This document provides an introduction to Python programming basics for beginners. It discusses Python features like being easy to learn and cross-platform. It covers basic Python concepts like variables, data types, operators, conditional statements, loops, functions, OOPs, strings and built-in data structures like lists, tuples, and dictionaries. The document provides examples of using these concepts and recommends Python tutorials, third-party libraries, and gives homework assignments on using functions like range and generators.
Go is an open source programming language designed by Google to be concurrent, garbage collected, and efficient. It has a simple syntax and is used by Google and others to build large distributed systems. Key features include garbage collection, concurrency with goroutines and channels, interfaces without inheritance, and a large standard library.
Go is a new systems programming language from Google. Go has many interesting features such as 'communication channels' that makes it suitable for use in multi-core machines, and network programming. With Ken Thompson (of Unix fame) as one of its designers, Go has elegant and minimal design that is appealing to most programmers. This talk gives a technical introduction to Go that is of interest to anyone working in system software.
[Presentation I have in 2010 - I haven't updated it with recent changes to the Go language]
GoLang is an open source programming language created by Google in 2009. It has a large community and was designed for scalability and concurrency. Some key features include being statically typed, compiled, and having built-in support for concurrency through goroutines and channels. Google uses GoLang extensively to build systems that scale to thousands of machines.
Esri International User Conference 2011: Python: Integrating Standard and Thi...jasonscheirer
This document summarizes a technical workshop on integrating standard and third-party Python libraries for use in ArcGIS. It discusses leveraging built-in Python libraries for common tasks like file I/O, networking, and data structures. It also covers finding and installing third-party libraries from the Python Package Index and providing examples of libraries for tasks like PDF generation, image processing, and Excel integration. The document emphasizes exploring Python's documentation and reusing existing libraries rather than reimplementing functionality.
Dart is an open-source programming language created by Google that compiles to JavaScript and allows developers to build web and server applications with a single language. Dart is easy to learn and comes with features like classes, interfaces, optional static types, lexical scoping, libraries, and isolates. It also includes a lightweight editor. A basic Dart program defines a printNumber function that prints a number, declares and initializes a variable, and calls the function to print the number. Dart code execution is supported in the browser via JavaScript compilation and on the server. The Dart team includes Lars Bak and Gilad Bracha who have experience with Java, JavaScript, and software patents.
This document outlines an agenda for a session on the Go programming language. It covers Go's history and development, grammar and syntax, concurrency features using CSP, the standard library and toolchain, interfacing Go with C, popular production and open source projects using Go, and reference materials. The session aims to provide an overview of Go's key features and how it is used in practice.
This document outlines the steps to train a custom object detection model using TensorFlow and Google Cloud Platform. It includes setting up prerequisites like TensorFlow and Google Cloud SDK, creating training datasets with images and annotations, converting data to TFRecord format, training a model using transfer learning on Cloud ML Engine, exporting the trained model, and testing the model.
SciPipe - A light-weight workflow library inspired by flow-based programmingSamuel Lampa
A presentation of the SciPipe workflow library, written in Go (Golang), inspired by Flow-based programming, at an internal workshop at Uppsala University, Department of Pharmaceutical Biosciences.
Using Aspects for Language Portability (SCAM 2010)lennartkats
This document discusses using aspects for language portability. It introduces four classes of portability aspects: 1) glue code aspects, 2) migration aspects, 3) integration aspects, and 4) optimization aspects. These aspects address additional portability issues beyond just replacing the backend, such as platform-specific libraries, unportable code, platform integration, and performance. Aspect-oriented programming is proposed as an elegant way to encapsulate platform-specific concerns in separate libraries.
Object oriented programming 7 first steps in oop using c++Vaibhav Khanna
Advantages of C++
Portability. C++ offers the feature of portability or platform independence which allows the user to run the same program on different operating systems or interfaces at ease. ...
Object-oriented. ...
Multi-paradigm. ...
Low-level Manipulation. ...
Memory Management. ...
Large Community Support. ...
Compatibility with C. ...
Scalability.
This document discusses the use of Python for geospatial applications. It describes Python as a programming language designed for beginners that has been integrated into ArcGIS and matured in ArcGIS 10. It provides examples of how Python is used with ArcGIS for tasks like standardizing school boundary data, analyzing wildlife photos, and creating spatial data packages. The conclusion encourages the use of Python for working with data and notes how the ArcPy library has matured for fast data access and useful Python toolboxes.
This document provides an overview of machine learning in Python using key Python libraries. It discusses popular Python libraries for machine learning like NumPy, SciPy, Pandas, Matplotlib and scikit-learn. It outlines the typical steps in a machine learning project including defining the problem, preparing and summarizing data, evaluating algorithms, and presenting results. It also introduces the Iris dataset as a sample classification dataset and discusses loading, handling and visualizing sample data for a machine learning project in Python.
When working with big data or complex algorithms, we often look to parallelize our code to optimize runtime. By taking advantage of a GPUs 1000+ cores, a data scientist can quickly scale out solutions inexpensively and sometime more quickly than using traditional CPU cluster computing. In this webinar, we will present ways to incorporate GPU computing to complete computationally intensive tasks in both Python and R.
See the full presentation here: 👉 https://vimeo.com/153290051
Learn more about the Domino data science platform: https://www.dominodatalab.com
This document discusses scaling R to large datasets using Scala and Akka. It describes how R has limitations for parallelism and handling large data in memory. The author demonstrates reading a large CSV file of 100 million doubles (1.7GB) in parallel using Scala, Akka actors and Rserve. Producer and Worker actors divide the file and sum parts in Rserve. This allows scaling R computations to large data beyond a single machine's memory. Potential applications mentioned include optimization, distributed linear algebra, machine learning and statistics.
This document provides an overview of ESRI and ArcGIS. It discusses that ESRI was founded in 1969 and began developing GIS tools in the 1980s, releasing their first commercial software ARC/INFO in 1982. It then summarizes the history of ArcGIS, including the releases of ArcView in the 1990s, ArcGIS 8.X in 1999, and ArcGIS 9.X in 2004. The document also outlines the different ArcGIS Desktop components and levels, as well as the industries where ArcGIS is applicable, such as agriculture, utilities, government, and more.
This document provides an overview of editing features in ArcGIS 10X. It discusses the changes to the editing interface and tools compared to previous versions. Key changes include the introduction of feature templates to define how features are constructed and attributed. It also covers the new Create Features window that combines the target layer and sketch tools. The document reviews the various feature construction tools available through the templates, toolbars, and editor menu. It provides details on how to edit existing feature vertices and sketches.
This document provides an overview of ArcGIS and its components. It discusses how data are stored in ArcGIS using different data models over time, including coverages, shapefiles, and geodatabases. It describes the main ArcGIS applications - ArcMap for viewing and editing data, ArcCatalog for data management, and ArcToolbox for geoprocessing tools. It also outlines some key ArcGIS extensions for spatial, geostatistical, and 3D analysis.
Este documento presenta la empresa Sanki y sus productos nutracéuticos BelAge y Kronuit. Resume que Sanki desarrolla productos utilizando nanotecnología y biotecnología avanzadas para mejorar la absorción de ingredientes antioxidantes. Los productos BelAge y Kronuit contienen extractos de romero y olivo que combaten el estrés oxidativo asociado con el envejecimiento. También presenta oportunidades para comercializar estos productos y ganar bonos.
Loading Parcels Into Smallworld GIS via FMESafe Software
This document discusses Puget Sound Energy's process for loading parcel data into their GE Smallworld GIS system using FME software. It covers PSE's history with parcel data, the current process of obtaining data from counties and transforming it using FME workbenches to address issues before loading it into Smallworld. Examples are provided of data issues from different counties and the FME solutions used to successfully load the data. Common data problems and future plans to streamline the interim parcel update process are also outlined.
Creating Excel files with Python and XlsxWriterjmncnamara
This document provides an overview of creating Excel files using the XlsxWriter Python module. It discusses available Python modules for working with Excel files, the different Excel file formats, and features supported by XlsxWriter like cell formatting, data types, formulas, images, conditional formatting, and charts. Examples are provided demonstrating how to write basic Excel files, format cells, add different data types to cells, write formulas, insert images, apply conditional formatting, and create different types of charts using XlsxWriter.
Avidgeo String Manipulation : Getting Started with Python and ArcGISGuido Stein
This is a presentation that teaches about making single line statements with python to manipulate string variables with a focus on esri arcgis calculate field. This presentation was given at the February 2013 AvidGeo Meetup group hosted by CGA Harvard. For more about the AvidGeo group visit their website at http://avidgeo.com
This tutorial familiarizes you with some basic features of ArcGIS and illustrates fundamentals of GIS. You will work with map layers and underlying attribute data tables for U.S. states, cities, counties, and streets. You will open an existing map document, save it to a new location, and learn how to work with map layers, navigate maps, measure distances, work with feature attributes, select features, and work with attribute tables. The goal is to introduce basic GIS concepts and skills.
The document discusses several GIS analysis tools and functions in ArcMap including adding XY data, buffering, selections, editing operations like sketching and modifying features, topology rules, and building a geometric network. Key steps are outlined for using tools like the buffer wizard, selections by location, sketch contexts, extending and trimming features, defining topology rules, and creating a geometric network by selecting layers and defining edges and junctions. Examples provided illustrate identifying buildings affected by road widening and selecting roads within or crossing a boundary.
This document provides a manual for basic GIS functions. It introduces ArcGIS components like ArcCatalog, ArcMap and ArcToolbox. It discusses importing and viewing data, creating shapefiles, and setting projections. It also covers georeferencing images, analyzing data through tools like clip and extract, and performing proximity analysis. The document aims to guide users through foundational GIS processes.
The document discusses the components of ArcGIS software. It describes ArcMap as the application for viewing, editing, creating, and analyzing geospatial data. ArcToolbox contains tools for tasks like data management and analysis. ArcCatalog provides tools for managing data, folders, metadata, and more. It also discusses concepts like map projections, spatial data formats, attribute tables, and performing selections and joins on data.
This is presentation is intended for middle school students. It provides a short introduction to GIS and how to use GIS in the real-world.
ArcGIS Explorer is the software used to demonstrate concepts.
45 minutes + 15 minutes demo
Download ArcGIS Explorer here...
http://www.esri.com/software/arcgis/explorer/
This document contains 25 quotes from Steve Jobs on a variety of topics. Some of the key themes that emerge are Jobs' focus on excellence and innovation, his belief that quality should take priority over quantity, and his vision that technology could be used to change people's lives. He also expressed confidence in Apple's future leadership and his ongoing connection to the company even if he wasn't present at all times.
Why Python Should Be Your First Programming LanguageEdureka!
This document discusses why Python should be the first programming language for learners. Python has a short learning curve due to its readability, lack of curly braces, and easy setup. It is a dynamic, object-oriented language with a large standard library that makes it suitable for tasks like data analysis, web development, scientific computing, and more. Many large companies like Google, YouTube, Dropbox, and Yahoo use Python for applications, tools, and internal projects. The popularity and demand for Python skills has grown significantly in recent years.
Introduction to python -easiest way to understand python for beginners
What is Python…?
Differences between programming and scripting language
Programming Paradigms
History of Python
Scope of Python
Why do people use Python?
Installing Python
Python is an object-oriented, high-level programming language that is easy to learn and use for a variety of purposes including web and app development, data analysis, automation, and more. It can be used on many platforms and has a simple syntax that focuses on readability. Python allows for rapid prototyping and is commonly used in fields like data science where it can handle large datasets. Key benefits include its productivity, readability, extensive standard library, and ability to be extended with additional modules.
This document provides an introduction to the Python programming language. It discusses that Python is an interpreted, object-oriented language that was first released in 1990 and was designed by Guido van Rossum. It also highlights that Python is easy to learn, readable, simple, and multipurpose. Examples of Python code and comparisons to R are provided. Popular online resources for learning Python are listed. The document also discusses Python's uses in areas like application development, web development, scientific computing, and more. Pros and cons of Python are outlined.
Build Real-World Mobile Applications With Python App Development Services Com...Cerebrum Infotech
Cerebrum Infotech offered the best Python app development services to our clients, it's a largely flexible language with numerous libraries and tools available. Please see our website for more information!
Migration of Applications to Python is the most prudent DecisionMindfire LLC
Python is one of the top 10 most popular programming languages of 2021, according to the latest PYPL Index. It’s a no-brainer that if you want your software to perform better in the long run- Python is the best choice. If you use a different language for your applications, you can consider moving your applications to Python.
Python was created in the late 1980s by Guido van Rossum as a successor to the ABC programming language. It uses dynamic typing and garbage collection for memory management. Key features include its clear syntax, object orientation, modularity through packages, and extensive standard libraries. Python code is highly readable and portable across operating systems.
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.
A slightly modified version of original "An introduction to Python
for absolute beginners" slides. For credits please check the second page. I used this presentation for my school's internal Python course. thank you forviewing
This document provides an introduction to the Python programming language. It discusses that Python was created by Guido Van Rossum in 1989. It is an interpreted, interactive, object-oriented language with simple syntax making it ideal for beginners. The document outlines Python's history, features, supported platforms, comparisons to other languages, popular uses and applications.
Python is a powerful and object-oriented programming language that has grown rapidly in popularity due to its simplicity and flexibility. It supports multiple programming paradigms and has a large standard library. Python source code is first compiled to bytecode, which is then executed by the Python Virtual Machine. While Java may be faster for single algorithms, Python is easier for beginners to learn and its dynamic typing and automatic memory management make programs quicker to write. It has gained widespread use for web development, data science, and scripting.
The document discusses using Python at the Chicago Stock Exchange (CHX). It provides an overview of Python, comparing it to Perl, and outlines CHX's structure for using Python. This includes building reusable modules for common tasks like connecting to Oracle databases, running jobs and procedures, and sending emails. An example project is described that extracted attachments from a database using a Python template with modules. The summary advocates considering Python for future programs due to its maintainability, scalability, and ease of adoption for developers from languages like Java and C++.
Mastering the Interview: 50 Common Interview Questions DemystifiedMalcolmDupri
Embark on your journey into the world of programming with this comprehensive introduction to Python. Whether you're a beginner eager to learn your first programming language or an experienced developer seeking to expand your skill set, this Slide Share presentation is the perfect starting point. From the basics of syntax and data types to more advanced concepts like functions and modules, we'll guide you through the fundamentals of Python programming in an accessible and engaging manner. By the end of this presentation, you'll have a solid understanding of Python's capabilities and be well-equipped to tackle a variety of programming challenges.
Python is an easy to learn programming language that is widely used for a variety of tasks. It has a simple syntax that allows developers to focus on solving problems rather than dealing with complex language features. Python code can be written quickly and read easily by others. It also has a large ecosystem of libraries and frameworks that support application development, data science, machine learning, and more. While not the fastest language, Python makes up for it with versatility and the ability to connect different systems through its "glue" programming capabilities.
Python is an interpreted, object-oriented, high-level programming language that emphasizes code readability. It has a large standard library, dynamic typing, and is available for free on all major platforms. Python supports multiple programming paradigms including procedural, object-oriented, and functional programming. It is commonly used for web development, scripting, and rapid application development due to its simple syntax and readability.
IRJET- Python: Simple though an Important Programming LanguageIRJET Journal
Python is an important and widely used programming language due to its simplicity, large standard library, and use in applications like machine learning and AI. It is easy for beginners to learn and use for both learning programming concepts and real-world applications. Many major companies like Google, Facebook, and NASA use Python extensively. While it has some disadvantages like speed, it is well-suited for tasks like data analysis, scientific computing, and web development. Its popularity and importance are increasing over time as it is applied to more domains like machine learning.
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Introduction to Python
What is Python?
Python is a high-level, interpreted programming language known for its simplicity and readability. It was created by Guido van Rossum and first released in 1991. Python emphasizes code readability with its clean and straightforward syntax, making it an excellent choice for beginners and experienced developers alike.
Features of Python:
Simple and Easy to Learn: Python's syntax is designed to be intuitive and readable, making it easy for beginners to grasp.
Interpreted: Python code is executed line by line by the Python interpreter, which means you can run Python code without the need for compilation.
High-Level: Python abstracts low-level details, allowing developers to focus on solving problems rather than dealing with system-level intricacies.
Dynamic Typing: Python uses dynamic typing, meaning you don't need to declare variable types explicitly. Variables can dynamically change types during execution.
Multi-paradigm: Python supports multiple programming paradigms, including procedural, object-oriented, and functional programming.
Extensive Standard Library: Python comes with a vast standard library that provides support for various tasks like file I/O, networking, and more, making it highly versatile.
Portability: Python is available on various platforms, including Windows, macOS, and Linux, making it highly portable.
Community and Ecosystem: Python has a large and active community, contributing to a rich ecosystem of libraries and frameworks for various domains, such as web development, data science, machine learning, and more.
Use Cases of Python:
Web Development: With frameworks like Django and Flask, Python is widely used for building web applications.
Data Science: Python's rich ecosystem of libraries such as NumPy, Pandas, and Matplotlib makes it a popular choice for data analysis and visualization.
Machine Learning and AI: Libraries like TensorFlow, PyTorch, and scikit-learn enable developers to build machine learning models and AI applications efficiently.
Scripting: Python's simplicity and versatility make it ideal for writing scripts for automation, system administration, and more.
Game Development: Python is used in game development, both for writing game logic and scripting within game engines like Unity.
Installing Python:
To get started with Python, you need to install it on your system. You can download Python from the official website python.org and follow the installation instructions for your operating system.
Hello, World! Example:
Let's start with the traditional "Hello, World!" program in Python:
python
Copy code
print("Hello, World!")
This simple program prints "Hello, World!" to the console. It's a common starting point for learning any programming language.
Python is a general purpose, dynamic, high level and interpreted programming language that is easy to learn yet powerful and versatile, making it attractive for application development. It supports multiple programming paradigms including object oriented, imperative and functional programming. Python is widely used for tasks like web development, machine learning, scientific computing, and more due to its large standard library and being cross-platform, free/open source, and having a simple syntax. People use Python because it is easy to learn and use, expressive, interpreted, cross-platform, free/open source, supports object oriented programming, is extensible, and has a large standard library and GUI programming support.
This document provides an overview of the Python programming language. It discusses Python's history, key features such as being easy to use, scalable, high-level, object-oriented, interpreted, and having a rich core library. It also covers Python's uses in areas like web development, databases, GUI programming, and more. The document is intended to introduce readers to Python and provide context for a book on making use of the language.
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1. How to enter the world of
Python Programming for ArcGIS
Or, a funny thing happened on the
way from an ESRI conference
By Katherine Paybins
WVAGP Membership Meeting, November 3, 2011
2. Why use Python in ArcGIS 9 or 10?
• With ArcGIS 10, Python scripting takes front place
for programming repetitive tasks and creating
custom functions for the ArcToolbox.
• Python as a programming language has been
around for awhile, and when your ArcGIS 10 was
installed, Python 2.6.5 was also, with a GUI
included called the Idle Python Shell. There are
other GUIs out there, but the Idle GUI is one of
the more popular for it’s ease of use.
3. From the Python Tutorial
• Python is an easy to learn, powerful programming language. It has
efficient high-level data structures and a simple but effective
approach to object-oriented programming. Python’s elegant syntax
and dynamic typing, together with its interpreted nature, make it
an ideal language for scripting and rapid application development in
many areas on most platforms.
• The Python interpreter and the extensive standard library are freely
available in source or binary form for all major platforms from the
Python Web site, http://www.python.org/, and may be freely
distributed. The same site also contains distributions of and
pointers to many free third party Python modules, programs and
tools, and additional documentation.
4.
5. From ESRI help documents
Python was introduced to the ArcGIS community at 9.0. Since then, it has been
accepted as the scripting language of choice for geoprocessing users and continues
to grow. Each release has furthered the Python experience, providing you with more
capabilities and a richer, more Python-friendly experience.
ESRI has fully embraced Python for ArcGIS and sees Python as the language that
fulfills the needs of our user community. Here are just some of the advantages of
Python:
Easy to learn and excellent for beginners, yet superb for experts
Highly scalable, suitable for large projects or small one-off programs known as
scripts
Portable, cross-platform
Embeddable (making ArcGIS scriptable)
Stable and mature
A large user community
Python extends across ArcGIS and becomes the language for data analysis, data
conversion, data management, and map automation, helping increase productivity.
10. Look at the ESRI site for sample scripts to download, and also
look within the ArcToolBox for scripts.
11.
12. Online classes
• The Python tutorial is available on several
sites, but you have it on your computer if you
have ArcGIS installed
• ESRI offers twelve online courses relating directly
to or referencing Python, including:
Basics of Python (for ArcGIS 10)
Python Scripting for Map Automation in ArcGIS 10
Python Scripting for Geoprocessing Workflows
(ArcGIS 10)
13. An example of learning the software
• First, conference sessions showing use of the new
arcpy set of python scripts
• Next, taking the tutorial and starting a notes for
future reference/ copy and paste into Python.
• Also, testing out running commands in the
Python window
• Purchased a couple of books on the topic- I like
the Python Phrasebook by Brad Dayley, and Core
Python Programming by Wesley Chun
• As I work on projects, I try to view any Python
scripts in the GeoProcessing tools
14. Taking notes is a good idea
For instance, here are some notes from the Tutorial that I have kept for
reference and cut/paste.
________________________________________________________
Commands to start at beginning of interactive Python session, or in a script if I
want the functionality included by using these commands.
import os
filename = os.environ.get('PYTHONSTARTUP')
if filename and os.path.isfile(filename):
execfile(filename)
import env
import arcpy
arcpy.sa
arcpy.mapping
arcpy.ga
15. An easy way to make a python program
from geoprocessing models: