Python programming - Everyday(ish) Examples

Download as pptx, pdf

2 likes1,521 views

The document provides an overview of common Python coding problems and their solutions, aimed at beginners familiar with Python concepts. It includes examples of calculating CGPA from SGPA, using data structures like dictionaries, applying regular expressions for data validation, and emphasizes the importance of unit testing in software development. Additionally, it offers resources for further learning, such as Codecademy and other Python guides.

Software

 Python is a programming language with strengths of both functional and object-oriented
programming.
 Here I will present common problems and their solutions that you might use while
starting coding in Python.
 You may use this material as a reference.
By Ashish Sharma for Next Craft

 One who has began learning Python.
 One who has made oneself acquainted with concepts of Python taught in
codecademy.com Python course.
 One who wishes to learn the idioms of python to solve problems in pythonic way.
 One who is interested in free, good content. 
By Ashish Sharma for Next Craft

 Learn by Doing: Here are examples of python code used in different scenarios.
 You can try to pick the concepts and then mould them to use in your own
situation.
 Use of Classes, Exceptions, rest of Standard Library not covered here.
By Ashish Sharma for Next Craft

 Let us suppose we have a file containing a student’s SGPAs from 8 semesters and
we would like to write a new file with CGPA.
 SGPA.txt , has list of numbers in different lines.
 Generating CGPA.txt from SGPA.txt
 We will first read the SGPA.txt file line by line,
 Then accumulate the values into a single variable,
 Then calculate CGPA value and write that back into a new file.
Try out yourself with sample
data
By Ashish Sharma for Next Craft

 Let us suppose you have a list of SGPAs on scale of 10 and from it you want to
calculate CGPA on scale of 4.
 We will do this in two ways,
 Using for loop,
 Using map, reduce (they are not as scary as they may sound)
 The ways of coding this by map, reduce etc. are less verbose and more
transportable.
By Ashish Sharma for Next Craft

Using for loop
By Ashish Sharma for Next Craft

Using Reduce
Using Map/Reduce
By Ashish Sharma for Next Craft

 In Python the data structure of Map is implemented in Dictionary.
 A map is a structure to store <key, value> relationships.
 Suppose you need to compute sum of squares of given odd numbers that can not
be smaller than 1 and larger than 99
 In the example, we will pre compute as the limits are small and return answers
from a dict.
By Ashish Sharma for Next Craft

 From the older sgpa example, if we wish to filter out the sgpa from list that were
more than 8.5.
 From the older odd_squares example, if we wish to filter out the odd squares
where the number is a multiple of 3.
By Ashish Sharma for Next Craft

 Here we will validate data sent our way with regular expressions. You can also use
them for search, match and replace.
 Suppose we want input from user to be a number, here is how to gracefully handle
this requirement.
By Ashish Sharma for Next Craft

 Unit testing is a very important aspect of software development. In Python, you
can find extensive support for unit testing you code.
 With unit testing we can test single functions, classes or whole modules.
 Having code and test separately and testable is a prime software development
requirement.
 This fact is elicited in this advice that developers get from creator of Unit testing
framework for Small talk, (one of the first or may be the first frameworks).
 I recommend that developers spend 25-50% of their time developing tests.
 Quoted from - http://www.xprogramming.com/testfram.htm
By Ashish Sharma for Next Craft

 Here is a sample of code and test files.
By Ashish Sharma for Next Craft

Please let me know in the comments if I am missing any general scenarios, which
you would like to see in the examples here.
I will be more than happy to extend this presentation.
By Ashish Sharma for Next Craft

 Python Reference – The best guide on Python out there.
 Codecademy – Beginner course on Python, totally free .
 http://learnpythonthehardway.org/ - If you want to develop a deep sense of
knowledge of Python, venture here.
By Ashish Sharma for Next Craft

Find me at @ashish424242 and @kartaa.
Checkout NextCraft’s JMP
By Ashish Sharma for Next Craft

KMP pattern searching allows efficient searching of a pattern within text by taking advantage of prefix matches. It works by pre-processing the pattern to construct a prefix table indicating the length of matching prefix for all prefixes of the pattern. During searching, when a mismatch occurs, it uses the prefix table to "skip" already compared prefix matches, avoiding repeating comparisons and allowing it to run in linear time O(n+m).

Logic programming in pythonPierre Carbonnelle

Logic programming in Python allows for productive, readable programs using logic rules rather than loops or conditionals. The pyDatalog library adds logic programming capabilities to Python. Programs are defined with facts and clauses like Prolog, and can query SQL databases. PyDatalog memoizes results to avoid recomputation and supports features like aggregate functions. It allows applications like spreadsheet programming, expert systems, and cross-database queries. The presenter outlines roadmaps for adding an equation solver, transactions, and improving performance.

Init() Day 4UCLA Association of Computing Machinery

Intro To BOOST.SpiritWill Shen

This document provides tutorials and examples for using Boost Spirit Qi, a C++ parsing library. It demonstrates how to parse numeric values, semantic actions, grammars, and structs. The tutorials include parsing floating point numbers, comma-separated lists, and attaching semantic actions. Examples show parsing complex numbers, adding numbers, parsing into vectors, Roman numerals, and a calculator grammar.

Python tutorialAndrei Tomoroga

- Python is an interpreted, dynamic and object-oriented programming language. It uses indentation rather than brackets to delimit blocks of code. Variables do not require declaration of type. - Python code is more readable and flexible compared to other languages. It allows for higher productivity without compile-time type checking. Code is checked at runtime by the Python interpreter. - The Python interpreter makes it good for learning the language and experimenting with libraries. Built-in functions like dir() and help() provide assistance.

libpinyinPeng Wu

The document discusses the background and current state of pinyin input methods (IMs) for Chinese text entry on Linux. It surveys existing open-source pinyin IMs like Fcitx, ibus-pinyin, and scim-pinyin, which use techniques like maximum forward match and uni-gram modeling. Sunpinyin and novel-pinyin are highlighted as NLP-based IMs that use n-gram and Hidden Markov models. The document proposes a new library called libpinyin that would merge the core functionality of sunpinyin and novel-pinyin to reduce duplication of efforts and provide a standardized pinyin processing library. Its goals are to make

Response to uspto on the first topic v5getsocialize

The document is Groklaw's response to the USPTO regarding functional claiming in software patents. It argues that claiming software functions without accompanying algorithms results in patents on inventions the patentee did not invent. It states algorithms should be detailed enough such that all functional elements have corresponding algorithms that are either explicitly disclosed or known in the prior art. Providing structure for functional language can reduce litigation but does not replace subject matter analysis.

Introduction to Structure Programming with C++Mohamed Essam

Functions allow code to be reused by grouping a series of statements together to perform a specific task. A function definition specifies the data types of parameters and return values, and the function body contains the statements. Functions are called by their name followed by parentheses, and actual arguments are passed inside the parentheses. Parameters act as variables that represent the arguments passed into the function.

Lets learn Python !Kiran Gangadharan

This document provides an introduction to the Python programming language. It discusses why Python is a good language to learn, as it is readable, powerful, productive, portable, and can be used for web development, data analysis, and more. Major companies and organizations like Google, YouTube, and NASA use Python. The creator of Python was Guido Van Rossum. The document concludes by inviting the reader to learn Python basics like Hello World, variables, control flow, and data structures.

Introduction to PythonNowell Strite

This document provides an introduction and overview of the Python programming language. It covers Python's history and key features such as being object-oriented, dynamically typed, batteries included, and focusing on readability. It also discusses Python's syntax, types, operators, control flow, functions, classes, imports, error handling, documentation tools, and popular frameworks/IDEs. The document is intended to give readers a high-level understanding of Python.

Python 4 Arcabsvis

This document provides an overview of using Python and the Geoprocessor object to automate geoprocessing tasks in ArcGIS. It discusses: 1) Converting multiple ASCII files to rasters, merging the rasters, reclassifying the data, and converting it to polygon and polyline shapefiles involves many manual steps. 2) Scripting can automate this repetitive process and save time compared to performing the tasks manually each time. 3) The Geoprocessor object in ArcGIS provides a single access point to the toolbox and its methods/properties can be used to programmatically run geoprocessing tools from Python scripts.

The Python Programming Language and HDF5: H5PyThe HDF-EOS Tools and Information Center

The document discusses the advantages of using Python, specifically through the h5py library, for processing satellite remote sensing data due to its flexibility and capability to handle both numerical and non-numerical tasks efficiently. It highlights Python's ease of use compared to traditional languages like Fortran and the importance of handling data provenance and customization in modern satellite processing systems. Furthermore, it provides practical examples demonstrating how to utilize Python and h5py for data aggregation and manipulation of HDF5 files.

Python in real world.[email protected]

Substituting HDF5 tools with Python/H5py scriptsThe HDF-EOS Tools and Information Center

The document discusses the limitations of traditional HDF5 command line tools and suggests using Python with the h5py library as a more flexible and efficient alternative for manipulating HDF5 files. It highlights Python's dynamic binding, scientific array support, and ease of use, making it suitable for HDF5 operations that require high-level manipulation. The document also recommends that users adopt Python for HDF5 tasks and that the HDF group focus on enhancing the API for object-level operations.

Introduction To Programming with Python-1Syed Farjad Zia Zaidi

The document outlines a programming class focused on Python, covering key concepts such as variables, functions, algorithms, and flow control. It includes definitions and examples of fundamental programming constructs, including the creation of a simple calculator and a mini-project for a rock-paper-scissors game. Additionally, it discusses the differences between source code and object code, as well as the role of compilers in programming.

Logic Over LanguagePurple, Rock, Scissors

The document discusses understanding programming concepts using pseudo-code, emphasizing logic over specific programming languages. It provides examples of how to implement a solution for issuing movie tickets to employees who RSVP, highlighting the roles of classes and methods in programming. The document concludes with further reading suggestions and contact information for Renee Blunt at Prpl HQ.

Python and HDF5: Overviewandrewcollette

The document discusses the integration of Python and HDF5 for managing scientific data, emphasizing flexibility, robustness, and ease of use. It highlights Python's extensive library ecosystem, including modules for numerical analysis, visualization, and interfacing with C libraries, as well as the features of HDF5 such as hierarchical data organization and self-describing capabilities. Real-world applications, including data from UCLA's Large Plasma Device, showcase the utility of this combination in scientific research and data visualization.

An Introduction to Interactive Programming in Python 2013Syed Farjad Zia Zaidi

Introduction to DatabasesSyed Farjad Zia Zaidi

Logic: Language and Information 1Syed Farjad Zia Zaidi

Introduction To Programming with Python-5Syed Farjad Zia Zaidi

Introduction To Programming with Python-4Syed Farjad Zia Zaidi

This document provides an introduction to using lists in Python. It defines what lists are in Python, how to create, access, update, and delete list elements, and some common list operations. It also provides examples of creating lists, accessing values at different indices, updating and deleting elements, and using basic operators like addition and multiplication. Finally, it proposes three exercises involving lists to practice these concepts.

Introduction to UBIRoy Lee

This document describes UBI (Unsorted Block Images), a volume management system for flash devices in Linux. It provides static and dynamic volumes, wear-leveling across the entire flash device, bad block management, and read disturbance handling. The key components of UBI are the kernel API, EBA (Erase Block Association) subsystem, wear-leveling subsystem, and scanning subsystem. The wear-leveling subsystem manages PEBs (Physical Erase Blocks) using RB-trees and a queue to perform wear leveling and scrubbing.

Clase 2 estatica Gerald Moreira Ramírez

La mecánica es la ciencia que estudia el movimiento y reposo de los cuerpos bajo la acción de fuerzas. Se divide en mecánica de cuerpos rígidos, deformables y fluidos. La mecánica de cuerpos rígidos se subdivide en estática, que estudia cuerpos en reposo, y dinámica, que estudia cuerpos en movimiento. La mecánica se remonta a Aristóteles y Newton y utiliza conceptos como fuerza, masa, espacio y tiempo.

PythonPurev-Oidov Gonchigsuren

Using HDF5 and Python: The H5py moduleThe HDF-EOS Tools and Information Center

This document discusses using Python with the H5py module to interact with HDF5 files. Some key points made include: - H5py allows HDF5 files to be manipulated as if they were Python dictionaries, with dataset names as keys and arrays as values. - NumPy provides array manipulation capabilities to work with the dataset values retrieved from HDF5 files. - Examples demonstrate reading and writing HDF5 datasets, comparing contents of datasets between files, and recursively listing contents of an HDF5 file. - Using Python with H5py is more concise than other languages like C/Fortran, reducing development time and potential for errors.

HDF5 ToolsThe HDF-EOS Tools and Information Center

The document provides an overview of HDF and HDF-EOS tools presented at the workshop from October 15-18, 2008, highlighting HDFView and various command line tools for HDF5 management. It details functionalities for data import, export, and manipulation, including examples of using tools like h5dump, h5diff, and h5repack. Additionally, the document covers new features and improvements in software versions, alongside statistics generation and file verification processes.

Beginning PythonAgiliq Info Solutions India Pvt Ltd

This document outlines an introductory workshop on Python programming. It instructs participants to install Python and an editor, and assumes some programming knowledge. It provides overviews of Python's dynamic and object-oriented nature, basic constructs like conditionals and loops, built-in data types like lists and dictionaries, functions, classes, file I/O, and popular Python libraries and frameworks. Examples include FizzBuzz, word counting, and using list comprehensions.

Python Part 1Mohamed Ramadan

Here is a Python function that calculates the distance between two points given their x and y coordinates: ```python import math def distance_between_points(x1, y1, x2, y2): return math.sqrt((x2 - x1)**2 + (y2 - y1)**2) ``` To use it: ```python distance = distance_between_points(1, 2, 4, 5) print(distance) ``` This would print 3.605551275463989, which is the distance between the points (1,2) and (4,5). The key steps are: 1.

Beginning PythonAgiliq Solutions

This document outlines an introductory workshop on Python programming. It discusses Python's core features like dynamic typing, object orientation, and support for multiple paradigms. It also covers basic syntax like variables, conditionals, loops, functions and classes. The workshop involves coding examples like FizzBuzz and analyzing text files. It highlights Python's extensive standard library and popular frameworks. Attendees are encouraged to ask questions to clarify any unclear concepts during the session.

More Related Content

Viewers also liked (19)

Lets learn Python !Kiran Gangadharan

Introduction to PythonNowell Strite

Python 4 Arcabsvis

The Python Programming Language and HDF5: H5PyThe HDF-EOS Tools and Information Center

Python in real world.[email protected]

Substituting HDF5 tools with Python/H5py scriptsThe HDF-EOS Tools and Information Center

Introduction To Programming with Python-1Syed Farjad Zia Zaidi

Logic Over LanguagePurple, Rock, Scissors

Python and HDF5: Overviewandrewcollette

An Introduction to Interactive Programming in Python 2013Syed Farjad Zia Zaidi

Introduction to DatabasesSyed Farjad Zia Zaidi

Logic: Language and Information 1Syed Farjad Zia Zaidi

Introduction To Programming with Python-5Syed Farjad Zia Zaidi

Introduction To Programming with Python-4Syed Farjad Zia Zaidi

Introduction to UBIRoy Lee

Clase 2 estatica Gerald Moreira Ramírez

PythonPurev-Oidov Gonchigsuren

Using HDF5 and Python: The H5py moduleThe HDF-EOS Tools and Information Center

HDF5 ToolsThe HDF-EOS Tools and Information Center

Lets learn Python !Kiran Gangadharan

Introduction to PythonNowell Strite

Python 4 Arcabsvis

The Python Programming Language and HDF5: H5PyThe HDF-EOS Tools and Information Center

Python in real world.[email protected]

Substituting HDF5 tools with Python/H5py scriptsThe HDF-EOS Tools and Information Center

Introduction To Programming with Python-1Syed Farjad Zia Zaidi

Logic Over LanguagePurple, Rock, Scissors

Python and HDF5: Overviewandrewcollette

An Introduction to Interactive Programming in Python 2013Syed Farjad Zia Zaidi

Introduction to DatabasesSyed Farjad Zia Zaidi

Logic: Language and Information 1Syed Farjad Zia Zaidi

Introduction To Programming with Python-5Syed Farjad Zia Zaidi

Introduction To Programming with Python-4Syed Farjad Zia Zaidi

Introduction to UBIRoy Lee

Clase 2 estatica Gerald Moreira Ramírez

PythonPurev-Oidov Gonchigsuren

Using HDF5 and Python: The H5py moduleThe HDF-EOS Tools and Information Center

HDF5 ToolsThe HDF-EOS Tools and Information Center

Similar to Python programming - Everyday(ish) Examples (20)

Beginning PythonAgiliq Info Solutions India Pvt Ltd

Python Part 1Mohamed Ramadan

Beginning PythonAgiliq Solutions

Python Workshop - Learn Python the Hard WayUtkarsh Sengar

This document provides an introduction to learning Python. It discusses prerequisites for Python, basic Python concepts like variables, data types, operators, conditionals and loops. It also covers functions, files, classes and exceptions handling in Python. The document demonstrates these concepts through examples and exercises learners to practice char frequency counting and Caesar cipher encoding/decoding in Python. It encourages learners to practice more to master the language and provides additional learning resources.

Introduction to python programming 1Giovanni Della Lunga

This document provides an introduction to Python including: - The major versions of Python and their differences - Popular integrated development environments for Python - How to set up Python environments using Anaconda and Eclipse - An overview of Python basics like variables, numbers, strings, lists, dictionaries, modules and functions - Examples of Python control flow structures like conditionals and loops

Introduction to Python For Diploma StudentsSanjaySampat1

The document provides an introduction to Python, covering its features, applications, and resources for learning. It discusses Python's data types, syntax, control structures, and key programming concepts, emphasizing its versatility for various fields like AI and data science. Additionally, it touches on how to install Python and the significance of proper naming conventions and style guides within the community.

Python basicsBladimir Eusebio Illanes Quispe

Introduction to PythonUC San Diego

The document is an introduction to Python, highlighting its dynamic typing, readability, and versatility across multiple programming paradigms. It covers various concepts such as basic data types, control structures, functions, classes, modules, and exception handling, along with practical examples. The tutorial aims to provide a comprehensive overview for learners and developers interested in using Python for various applications.

1P13 Python Review Session Covering various Topicshussainmuhd1119

The document outlines the agenda for a Python review session hosted by the Google Developer Student Clubs at McMaster University, covering essential topics such as data types, functions, loops, object-oriented programming, and exception handling. It also includes explanations of built-in functions, common list and string methods, recursion, and OOP principles like encapsulation and inheritance. Furthermore, it emphasizes the importance of exception handling to ensure stable program execution and includes a link for additional resources.

Introduction to the intermediate Python - v1.1Andrei KUCHARAVY

The document discusses various programming practices and principles, focusing on coding in Python, including the importance of code simplicity, abstraction, and maintainability. It emphasizes the balance between complexity and manageability in software development, outlining pitfalls like spaghetti code and advocating for better documentation and code reuse. Additionally, it covers Python-specific features and idioms, including the use of decorators, higher-order functions, and functional programming concepts.

Data Structure and Algorithms (DSA) with Pythonepsilonice

This training report on 'DSA with Python' presents a comprehensive overview of data structures and algorithms, covering foundational elements like linked lists and stacks to more advanced structures such as trees and graphs. The report, submitted for a Bachelor of Technology degree, acknowledges guidance received from faculty and details various algorithms including sorting, searching, and graph traversal techniques. It serves as a practical application of Python programming concepts and object-oriented programming principles in the exploration of data structures and algorithms.

Talk CodeAgiliq Solutions

This document summarizes a presentation on Python programming. It introduces key Python concepts like data types, control structures, functions, classes, file handling and the standard library. It demonstrates these concepts through examples and encourages participants to try solving problems. The presentation also discusses functional programming with list comprehensions, object-oriented programming with classes, and web development frameworks like Django. Finally, it suggests additional Python modules like PIL, Mechanize and Beautiful Soup and provides resources for further learning.

Learn python in 20 minutesSidharth Nadhan

This document provides a comprehensive introduction to Python programming, covering basic syntax, string manipulation methods, control structures, data structures (lists, tuples, dictionaries), file I/O, functions, regular expressions, and command line arguments. It also includes examples of using modules for various tasks, the history of Python's creation, and the Zen of Python principles. The content serves as a guide for beginners looking to quickly learn Python within a short amount of time.

An Introduction : PythonRaghu Kumar

GE3151_PSPP_UNIT_5_NotesGuru Nanak Technical Institutions

This document outlines the objectives and units of study for the course GE3151 Problem Solving and Python Programming. The course aims to teach algorithmic problem solving using Python conditionals, loops, functions, and data structures like lists, tuples and dictionaries. Students will learn to do input/output with files in Python. The 5 units cover computational thinking and problem solving, Python data types and statements, control flow and functions, lists, tuples and dictionaries, and files, modules and packages. Key concepts covered include algorithms, conditionals, iteration, functions, strings, lists, files operations like reading, writing and closing files, and exception handling.

A quick python_tourcghtkh

This document provides an overview of the Python programming language. It describes that Python is an object-oriented, dynamically typed language that can be used for scripting, rapid prototyping, text processing, web applications, games, databases, and more. It then demonstrates Python's built-in data types like integers, floats, strings, lists, tuples, and dictionaries. Finally, it shows Python's control structures like conditionals, loops, functions, classes and objects.

ppt_pspp.pdfShereenAhmedMohamed

This document provides an overview of the Python programming language. It discusses Python's history and design, data types like integers, floats, strings, lists, tuples and dictionaries. It also covers core concepts like variables, expressions, control flow with if/else statements and loops. The document demonstrates how to take user input, read and write files, and describes moving Python code to files to make it reusable.

Python-languageinterview -Questions-A-Comprehensive-Guide.pptxnathvansh89

This document provides a comprehensive guide to Python language interview questions, covering essential concepts like data types, control structures, functions, and object-oriented programming. It emphasizes the importance of regular practice, understanding problem requirements, and writing efficient code for coding challenges. The conclusion encourages continued learning and exploration of advanced Python topics and libraries.

Processing data with Python, using standard library modules you (probably) ne...gjcross

The document is a tutorial from PyCon AU 2012 by Graeme Cross focused on processing data with Python using its standard library modules, specifically aimed at users familiar with Python 2.7. It covers essential topics such as Python data containers, iterators, comprehensions, and demonstrates various examples like analyzing Olympic medal results and managing data structures. Emphasis is placed on practical coding by using interactive demos and providing resources for further learning.

Python-content-1.pdfpanimalarhemdochemla

This document provides an introduction to a book about problem solving and Python programming. It contains the preface, introduction, table of contents, and list of authors. The preface explains that the book teaches how to understand and create computer programs in Python to solve problems in any area of interest. It uses plain language and step-by-step explanations. The introduction provides an overview of Python as a programming language that is widely used both professionally and educationally. It then lists the authors of the book. The table of contents outlines the 5 units that will be covered in the book.

Beginning PythonAgiliq Info Solutions India Pvt Ltd

Python Part 1Mohamed Ramadan

Beginning PythonAgiliq Solutions

Python Workshop - Learn Python the Hard WayUtkarsh Sengar

Introduction to python programming 1Giovanni Della Lunga

Introduction to Python For Diploma StudentsSanjaySampat1

Python basicsBladimir Eusebio Illanes Quispe

Introduction to PythonUC San Diego

1P13 Python Review Session Covering various Topicshussainmuhd1119

Introduction to the intermediate Python - v1.1Andrei KUCHARAVY

Data Structure and Algorithms (DSA) with Pythonepsilonice

Talk CodeAgiliq Solutions

Learn python in 20 minutesSidharth Nadhan

An Introduction : PythonRaghu Kumar

GE3151_PSPP_UNIT_5_NotesGuru Nanak Technical Institutions

A quick python_tourcghtkh

ppt_pspp.pdfShereenAhmedMohamed

Python-languageinterview -Questions-A-Comprehensive-Guide.pptxnathvansh89

Processing data with Python, using standard library modules you (probably) ne...gjcross

Python-content-1.pdfpanimalarhemdochemla

Recently uploaded (20)

CodeCleaner: Mitigating Data Contamination for LLM Benchmarkingarabelatso

Simplify Insurance Regulations with Compliance Management SoftwareInsurance Tech Services

Sap basis role in public cloud in s/4hana.pptxhtmlprogrammer987

CodeCleaner: Mitigating Data Contamination for LLM Benchmarkingarabelatso

Y - Recursion The Hard Way GopherCon EU 2025Eleanor McHugh

In most modern programming languages, including Go, it's possible for a function to call itself recursively. It's such a mainstream technique that we've come to take it for granted. But what if functions couldn't call themselves? There's a branch of mathematics called Combinatorics which answers just these kinds of questions, and this presentation takes these ideas and phrases them in Go to teach a deeper view of computation through the medium of code.

Sysinfo OST to PST Converter InfographicSysInfo Tools

Foundations of Marketo Engage - Programs, Campaigns & Beyond - June 2025BradBedford3

Join us for an exciting introductory session on, Foundations of Marketo Engage: Programs, Campaigns & Beyond. Ideal for new and early-stage users looking to build confidence and capability in Marketo Engage. Our speakers for this session will be: AJ Navarro Marketing Operations Manager - Sprout Social Bobby Coppola Marketing Manager - Blue Yonder This event will guide you through the essential steps to build strong, scalable Programs, Channels, Tags, Smart Campaigns, and Reporting Basics in Marketo Engage. Attendees will gain practical knowledge on how to structure and launch marketing initiatives, leverage templates for efficiency, and implement best practices for campaign execution and measurement. You'll leave with actionable insights you can immediately apply to your own Marketo instance to improve organization, automation, and reporting. Marketo Engage. Learn how to create impactful programs and understand the best practices for seamless campaign management and effective reporting. Don’t miss out on this opportunity to gain hands-on guidance from experienced practitioners and to connect with peers who are also new to the platform. Secure your spot today and start building your path to becoming a Marketo pro! Please feel free to invite colleagues who you think would also benefit from this session.

Azure AI Foundry: The AI app and agent factoryMaxim Salnikov

Discover how Azure AI Foundry is transforming the way organizations innovate and operate. This session explores the pivotal role of AI in reshaping business processes, enhancing employee experiences, and redefining customer engagement. Attendees will gain insights into the strategic value of AI investments, including the measurable returns and the growing momentum behind generative AI experimentation. The talk introduces the emerging paradigm of agentic AI - intelligent agents that are revolutionizing how we build, manage, and interact with software. Through real-world examples, the session demonstrates how Azure AI Foundry empowers teams to design, customize, and scale AI applications and agents, unlocking new levels of efficiency and creativity across industries.

ERP Systems in the UAE: Driving Business Transformation with Smart Solutionsdheeodoo

ERP solutions are driving innovative change for businesses across the UAE through improved efficiency, reduced operational costs, and provide real-time visibility of operational data. By offering native Arabic language support, VAT compliance, and some level of cloud readiness, ERP solutions also supports and are consistent with the initiative for Smart Dubai 2030. Odoo is an example of a flexible & scalable solution. If you're looking for expert support with implementation contact Banibro. www.banibro.com

Building Geospatial Data Warehouse for GIS by GIS with FMESafe Software

Data warehouses are often considered the backbone of data-driven decision-making. However, traditional implementations can struggle to meet the iterative and dynamic demands of GIS operations, particularly for Iterative Cross-Division Data Integration (ICDI) processes. At WVDOT, we faced this challenge head-on by designing a Geospatial Data Warehouse (GDW) tailored to the needs of GIS. In this talk, we’ll share how WVDOT developed a metadata-driven, SESSI-based (Simplicity, Expandability, Spatiotemporality, Scalability, Inclusivity) GDW that transforms how we manage and leverage spatial data. Key highlights include: - Simplifying data management with a lean schema structure. - Supporting ad hoc source data variations using JSON for flexibility. - Scaling for performance with RDBMS partitioning and materialized views. - Empowering users with FME Flow-based self-service metadata tools.We’ll showcase real-world use cases, such as pavement condition data and LRS-based reporting, and discuss how this approach is elevating GIS as an integrative framework across divisions. Attendees will walk away with actionable insights on designing GIS-centric data systems that combine the best of GIS and data warehouse methodologies.

Simplify Task, Team, and Project Management with Orangescrum WorkOrangescrum

Humans vs AI Call Agents - Qcall.ai's Special ReportUdit Goenka

Humans vs Agentic AI Cost Comparison: Cut 85% Support Costs TL;DR: Agentic AI crushes human costs in L1/L2 support with 85% savings, 300% efficiency gains, and 90%+ success rates. Your CFO just asked: "Why spend $2.3M annually on L1 support when competitors automated 80% for under $200K?" The humans vs agentic AI cost debate isn't theoretical - it's happening now. Real Cost Breakdown: - India L1/L2 Agent: ₹6,64,379 ($8,000) annually (full cost) - US L1/L2 Agent: $70,000 annually (loaded cost) - Qcall.ai Agentic AI: ₹6/min ($0.07/min) = 85% savings Game-Changing Results: - 47 human agents → 8 agents + AI system - Operating costs: $2.8M → $420K (85% reduction) - Customer satisfaction: 78% → 91% - First call resolution: 72% → 94% - Languages: 2-3 → 15+ fluently Why Agentic AI Wins: - Human Limitations: 8hrs/day, 1-2 languages, 30-45% attrition, mood-dependent, 6-12 weeks training - Qcall.ai Advantages: 24/7 availability, 97% humanized voice, <60 second response, intelligent qualification, seamless handoff Industry Impact: - E-commerce: 82% cost reduction - Healthcare: 90% appointment automation - SaaS: 23% satisfaction improvement - Financial: 95% inquiry automation Implementation: - Setup: 2-5 days vs 6-12 weeks hiring - ROI: Break-even in 3 months - Scaling: Instant global expansion Competitive Gap: - Early Adopters: 85% cost advantage, superior metrics, faster expansion Late Adopters: Higher costs, limited scalability, compounding disadvantage Similar automation patterns emerge across industries. Marketing teams use autoposting.ai for social media automation - same human-AI collaboration model driving L1/L2 transformation. "We reduced support costs by 78% while improving satisfaction by 31%. ROI was immediate and keeps compounding." - COO, Global SaaS Company Getting Started: Calculate current L1/L2 costs Assess repetitive tasks Request Qcall.ai demo Plan 20% pilot Bottom Line: Companies avoiding this shift hemorrhage millions while competitors scale globally with fraction of costs. The question isn't whether agentic AI will replace routine tasks - it's whether you'll implement before competitors gain insurmountable advantage. Ready to transform operations? This reveals complete cost analysis, implementation strategy, and competitive advantages.

Zoho Creator Solution for EI by Elsner Technologies.docxElsner Technologies Pvt. Ltd.

Best AI-Powered Wearable Tech for Remote Health Monitoring in 2025SEOLIFT - SEO Company London

arctitecture application system design os dsaza241967

Advance Doctor Appointment Booking App With Online PaymentAxisTechnolabs

AI for PV: Development and Governance for a Regulated IndustryBiologit

Threat Modeling a Batch Job Framework - Teri Radichel - AWS re:Inforce 20252nd Sight Lab

This presentation is similar to another presentation I gave earlier in the year at the AWS Community Security Day, except that I had less time to present and incorporated some AI slides into the presentation. In this presentation I explain what batch jobs are, how to use them, and that AI Agents are essentially batch jobs. All the same security controls that apply to batch jobs also apply to AI agents. In addition, we have more concerns with AI agents because AI is based on a statistical model. That means that depending on where and how AI is used we lose some of the reliability that we would get from a traditional batch job. That needs to be taken into consideration when selecting how and when to use AI Agents as batch jobs and whether we should use AI to trigger an Agent. As I mention on one side - I don't want you to predict what my bank statement should look like. I want it to be right! By looking at various data breaches we can determine how those attacks worked and whether the system we are building is susceptible to a similar attack or not.

IDM Crack with Internet Download Manager 6.42 Build 41 [Latest 2025]pcprocore

👉Copy link &paste Google new tab > https://pcprocore.com/ 👈✅ IDM Crack with Internet Download Manager (IDM) is a tool to increase download speeds, resume, and schedule downloads.Comprehensive error recovery and resume capability will restart broken or interrupted downloads due to lost connections, network problems, computer shutdowns, or unexpected power outages. The simple graphic user interface makes IDM user-friendly and easy to use. Internet Download Manager has a smart download logic accelerator with intelligent dynamic file segmentation and safe multipart downloading technology to accelerate your downloads. Unlike other download managers and accelerators, Internet Download Manager segments downloaded files dynamically during the download process and reuses available connections without additional connect and login stages to achieve the best acceleration performance for IDM users. System Requirements of IDM: Operating System: Windows XP, NT, 2000, Vista, 7, 8, 8.1, 10 & 11 (32bit and 64bit) Memory (RAM): 512 MB of RAM required Hard Disk Space: 25 MB of free space required for full installation Processor: Intel Pentium 4 Dual Core GHz or higher. Ensure your system meets these requirements for the IDM Crack to function properly. How to Install and Crack: Temporarily disable the antivirus until the IDM Crack process Install “idman642build41.exe” Extract “IDM 6.42.41 Patch.rar” (Password is: 123) Install “IDM 6.42.41 Patch.exe” Done!!! Enjoy!!!

OpenChain Webinar - AboutCode - Practical Compliance in One Stack – Licensing...Shane Coughlan

CodeCleaner: Mitigating Data Contamination for LLM Benchmarkingarabelatso

Simplify Insurance Regulations with Compliance Management SoftwareInsurance Tech Services

Sap basis role in public cloud in s/4hana.pptxhtmlprogrammer987

CodeCleaner: Mitigating Data Contamination for LLM Benchmarkingarabelatso

Y - Recursion The Hard Way GopherCon EU 2025Eleanor McHugh

Sysinfo OST to PST Converter InfographicSysInfo Tools

Foundations of Marketo Engage - Programs, Campaigns & Beyond - June 2025BradBedford3

Azure AI Foundry: The AI app and agent factoryMaxim Salnikov

ERP Systems in the UAE: Driving Business Transformation with Smart Solutionsdheeodoo

Building Geospatial Data Warehouse for GIS by GIS with FMESafe Software

Simplify Task, Team, and Project Management with Orangescrum WorkOrangescrum

Humans vs AI Call Agents - Qcall.ai's Special ReportUdit Goenka

Zoho Creator Solution for EI by Elsner Technologies.docxElsner Technologies Pvt. Ltd.

Best AI-Powered Wearable Tech for Remote Health Monitoring in 2025SEOLIFT - SEO Company London

arctitecture application system design os dsaza241967

Advance Doctor Appointment Booking App With Online PaymentAxisTechnolabs

AI for PV: Development and Governance for a Regulated IndustryBiologit

Threat Modeling a Batch Job Framework - Teri Radichel - AWS re:Inforce 20252nd Sight Lab

IDM Crack with Internet Download Manager 6.42 Build 41 [Latest 2025]pcprocore

OpenChain Webinar - AboutCode - Practical Compliance in One Stack – Licensing...Shane Coughlan

Python programming - Everyday(ish) Examples

1. Examples in Python

2.  Python is a programming language with strengths of both functional and object-oriented programming.  Here I will present common problems and their solutions that you might use while starting coding in Python.  You may use this material as a reference. By Ashish Sharma for Next Craft

3.  One who has began learning Python.  One who has made oneself acquainted with concepts of Python taught in codecademy.com Python course.  One who wishes to learn the idioms of python to solve problems in pythonic way.  One who is interested in free, good content.  By Ashish Sharma for Next Craft

4.  Learn by Doing: Here are examples of python code used in different scenarios.  You can try to pick the concepts and then mould them to use in your own situation.  Use of Classes, Exceptions, rest of Standard Library not covered here. By Ashish Sharma for Next Craft

5.  Let us suppose we have a file containing a student’s SGPAs from 8 semesters and we would like to write a new file with CGPA.  SGPA.txt , has list of numbers in different lines.  Generating CGPA.txt from SGPA.txt  We will first read the SGPA.txt file line by line,  Then accumulate the values into a single variable,  Then calculate CGPA value and write that back into a new file. Try out yourself with sample data By Ashish Sharma for Next Craft

6. Code By Ashish Sharma for Next Craft

7.  Let us suppose you have a list of SGPAs on scale of 10 and from it you want to calculate CGPA on scale of 4.  We will do this in two ways,  Using for loop,  Using map, reduce (they are not as scary as they may sound)  The ways of coding this by map, reduce etc. are less verbose and more transportable. By Ashish Sharma for Next Craft

8. Using for loop By Ashish Sharma for Next Craft

9. Using Reduce Using Map/Reduce By Ashish Sharma for Next Craft

10.  In Python the data structure of Map is implemented in Dictionary.  A map is a structure to store <key, value> relationships.  Suppose you need to compute sum of squares of given odd numbers that can not be smaller than 1 and larger than 99  In the example, we will pre compute as the limits are small and return answers from a dict. By Ashish Sharma for Next Craft

11. Code. By Ashish Sharma for Next Craft

12.  From the older sgpa example, if we wish to filter out the sgpa from list that were more than 8.5.  From the older odd_squares example, if we wish to filter out the odd squares where the number is a multiple of 3. By Ashish Sharma for Next Craft

13.  Here we will validate data sent our way with regular expressions. You can also use them for search, match and replace.  Suppose we want input from user to be a number, here is how to gracefully handle this requirement. By Ashish Sharma for Next Craft

14.  Unit testing is a very important aspect of software development. In Python, you can find extensive support for unit testing you code.  With unit testing we can test single functions, classes or whole modules.  Having code and test separately and testable is a prime software development requirement.  This fact is elicited in this advice that developers get from creator of Unit testing framework for Small talk, (one of the first or may be the first frameworks).  I recommend that developers spend 25-50% of their time developing tests.  Quoted from - http://www.xprogramming.com/testfram.htm By Ashish Sharma for Next Craft

15.  Here is a sample of code and test files. By Ashish Sharma for Next Craft

16. Please let me know in the comments if I am missing any general scenarios, which you would like to see in the examples here. I will be more than happy to extend this presentation. By Ashish Sharma for Next Craft

17.  Python Reference – The best guide on Python out there.  Codecademy – Beginner course on Python, totally free .  http://learnpythonthehardway.org/ - If you want to develop a deep sense of knowledge of Python, venture here. By Ashish Sharma for Next Craft

18. Find me at @ashish424242 and @kartaa. Checkout NextCraft’s JMP By Ashish Sharma for Next Craft

Python programming - Everyday(ish) Examples

Recommended

More Related Content

Viewers also liked (19)

Similar to Python programming - Everyday(ish) Examples (20)

Recently uploaded (20)

Python programming - Everyday(ish) Examples