در این جلسه از کلاس به ساختار های داده
Set, Tuple, Dictionary
پرداختیم
PySec101 Fall 2013 J3E1 By Mohammad Reza Kamalifard
Talk About :
Sets,Tuples and Dictionary Data Types in Python
The document provides an introduction to Python including:
- Starting the Python interpreter and basic calculations
- Variables, expressions, statements, functions, modules, comments
- Strings, lists, tuples, dictionaries
- Common list, string, and dictionary methods
It covers the basic Python syntax and many common data structures and their associated methods in less than 3 sentences.
The document provides an introduction to Python including:
- Starting the Python interpreter and basic calculations
- Variables, expressions, statements, functions, modules, comments
- Strings, lists, tuples, dictionaries
- Common list, string, and dictionary methods
It covers the basic Python syntax and many common data structures and their associated methods in less than 3 sentences.
The document provides examples and explanations of Python concepts including:
1. Printing "Hello World" with a function.
2. Using lists, including accessing/setting values and adding/removing elements.
3. Using range to generate lists of numbers.
4. Creating and manipulating dictionaries.
5. Logical operators and if/else statements.
6. For loops for iterating over lists and ranges.
7. Defining recursive functions.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
PLOTCON NYC: Behind Every Great Plot There's a Great Deal of WranglingPlotly
If you are struggling to make a plot, tear yourself away from stackoverflow for a moment and ... take a hard look at your data. Is it really in the most favorable form for the task at hand? Time and time again I have found that my visualization struggles are really a symptom of unfinished data wrangling. R has long had excellent facilities for data aggregation or "split-apply-combine": split an object into pieces, compute on each piece, and glue the result back together again. Recent developments, especially in the purrr package, have made "split-apply-combine" even easier and more general. But this requires a certain comfort level with lists, especially with lists that are columns inside a data frame. This is unfamiliar to most of us. I give an overview of this set of problems and match them up with solutions based on grouped, nested, and split data frames.
The document contains SQL scripts that create and modify databases and tables. It creates a LOGISTICA database, detaches and modifies the ALMACEN database, creates a CATEGORIAS table, expands data files, renames the database to VENTAS, and defines stored procedures to perform calculations.
The document discusses clustering and numpy arrays in Python. It shows how to create arrays using numpy, perform operations like summing and finding min/max values, and access elements and slices. It also introduces Cython and demonstrates compiling a simple "Hello World" Cython program and using Cython to optimize a Python prime number generation function for improved performance.
The document discusses the deque collection in Python. Some key points:
- Deque allows fast appends and pops from either side of the list, with O(1) time complexity, unlike regular lists which are slow (O(n)) for pop(0) and insert(0,v).
- Deque provides methods like append, appendleft, popleft, pop for adding/removing elements from either side of the list.
- It can be initialized with a maximum length to act as a sliding window, discarding old elements as new ones are added.
- Methods like rotate rotate the deque a given number of positions, extending adds multiple elements at once. Deque is useful when
The document provides an introduction to Python including:
- Starting the Python interpreter and basic calculations
- Variables, expressions, statements, functions, modules, comments
- Strings, lists, tuples, dictionaries
- Common list, string, and dictionary methods
It covers the basic Python syntax and many common data structures and their associated methods in less than 3 sentences.
The document provides an introduction to Python including:
- Starting the Python interpreter and basic calculations
- Variables, expressions, statements, functions, modules, comments
- Strings, lists, tuples, dictionaries
- Common list, string, and dictionary methods
It covers the basic Python syntax and many common data structures and their associated methods in less than 3 sentences.
The document provides examples and explanations of Python concepts including:
1. Printing "Hello World" with a function.
2. Using lists, including accessing/setting values and adding/removing elements.
3. Using range to generate lists of numbers.
4. Creating and manipulating dictionaries.
5. Logical operators and if/else statements.
6. For loops for iterating over lists and ranges.
7. Defining recursive functions.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
PLOTCON NYC: Behind Every Great Plot There's a Great Deal of WranglingPlotly
If you are struggling to make a plot, tear yourself away from stackoverflow for a moment and ... take a hard look at your data. Is it really in the most favorable form for the task at hand? Time and time again I have found that my visualization struggles are really a symptom of unfinished data wrangling. R has long had excellent facilities for data aggregation or "split-apply-combine": split an object into pieces, compute on each piece, and glue the result back together again. Recent developments, especially in the purrr package, have made "split-apply-combine" even easier and more general. But this requires a certain comfort level with lists, especially with lists that are columns inside a data frame. This is unfamiliar to most of us. I give an overview of this set of problems and match them up with solutions based on grouped, nested, and split data frames.
The document contains SQL scripts that create and modify databases and tables. It creates a LOGISTICA database, detaches and modifies the ALMACEN database, creates a CATEGORIAS table, expands data files, renames the database to VENTAS, and defines stored procedures to perform calculations.
The document discusses clustering and numpy arrays in Python. It shows how to create arrays using numpy, perform operations like summing and finding min/max values, and access elements and slices. It also introduces Cython and demonstrates compiling a simple "Hello World" Cython program and using Cython to optimize a Python prime number generation function for improved performance.
The document discusses the deque collection in Python. Some key points:
- Deque allows fast appends and pops from either side of the list, with O(1) time complexity, unlike regular lists which are slow (O(n)) for pop(0) and insert(0,v).
- Deque provides methods like append, appendleft, popleft, pop for adding/removing elements from either side of the list.
- It can be initialized with a maximum length to act as a sliding window, discarding old elements as new ones are added.
- Methods like rotate rotate the deque a given number of positions, extending adds multiple elements at once. Deque is useful when
The document provides information on arrays and hashes in Ruby. It discusses that arrays are ordered lists that can contain objects, and hashes are collections of key-value pairs. It then provides examples of creating, accessing, and modifying arrays and hashes. It also discusses various methods for iterating over arrays and hashes, such as each, collect, and each_pair.
This document discusses building an inverted index to search text documents. It shows how to tokenize documents into words, build a postings list to map words to the documents that contain them, and use the postings list to search for words in documents. It also discusses additional enhancements like handling punctuation, stemming, stop words, and storing more metadata with postings.
Functional programming languages promise to be easier to test and easier to debug. However, when learning the functional way we often try to translate our current techniques to another language. This is usually not easy and the end result is far from those promises we've heard. Early frustrations might even discourage from further learning.
In this talk I will show you two very simple patterns:
- Designing code around single data structure
- Dealing with impure parts of program like DBs, external services or IO
This should give beginners jump start for their first toy projects and further exploration.
This document provides an overview of lists in Python. It defines lists as ordered, mutable sequences that can contain elements of different data types. Key features covered include: lists allow duplicates, are indexed and sliced, can be modified via assignment, support common operations like membership testing and iteration. Examples are provided for list construction, accessing/replacing items by index, slicing subsets, checking if an item exists, and looping through lists.
This document provides a 5 minute summary of key Python concepts including variables, data types, conditionals, loops, functions, classes and modules. It demonstrates how to define and use integers, floats, strings, booleans, lists, tuples, dictionaries and sets. It also shows the syntax for if/else statements, for/while loops, functions, lambda functions, classes and importing/using modules in Python.
This document provides an introduction to the Elixir programming language. It discusses what Elixir is, how to get started with installation and configuration of Elixir and Erlang, basic and compound data types in Elixir, functions and modules, and higher-order functions and comprehensions. Key topics covered include installing Elixir using ASDF, basic data types like integers, floats, atoms, and more, functions and anonymous functions, modules, and Enum functions like map, reduce, and comprehensions.
PromptWorks Talk Tuesdays: Ray Zane 1/17/17 "Elixir Is Cool"PromptWorks
The document shows examples of pattern matching, case expressions, macros, and queries in Elixir. It demonstrates matching on different data types like lists, maps, tuples, and structs. It also shows examples of macros, case expressions, queries, and defining functions with pattern matching.
This SQL stored procedure performs a multi-step personnel search based on various criteria. It begins with an initial standard search, then applies additional filters for user tags, available dates, contracts, text searches, certification requirements, and personnel statuses to refine the results into a final output table. Temporary tables and dynamic SQL statements are used to sequentially apply each filter and move the results to the next stage.
- The document demonstrates various commands for exploring and summarizing data in R such as the iris data set including head(), tail(), str(), class(), summary(), and $-operator.
- The iris data set contains measurement data for 150 flowers across 4 variables and is stored as a data frame object in R.
- Data frames allow storing different data types together and can be explored using commands like summary() which provides summaries tailored to each variable type.
- Matrices can also be used to store multi-dimensional data and various functions like dim(), apply(), and cbind() allow manipulating the dimensions and combining matrices.
The document discusses using the Paco parsing library in Elixir. It shows how to define parsers for literals, sequences, repetitions, alternatives and more. It also demonstrates parsing expressions, references to elements with quantities, and converting terms to parsers via a Parsable protocol.
The document contains code examples demonstrating various Elixir concepts like defining modules and functions, pattern matching, pipes, macros, and more. It shows interactive sessions in IEx testing concepts like strings, binaries, lists, tuples, pattern matching, recursion, comprehensions, and more. Some examples include defining a module to calculate factorials recursively, working with binaries and binary patterns, building a poker hand evaluator, and using quote and unquote in macros.
Elixir & Phoenix – fast, concurrent and explicitTobias Pfeiffer
Elixir and Phoenix are known for their speed, but that’s far from their only benefit. Elixir isn’t just a fast Ruby and Phoenix isn’t just Rails for Elixir. Through pattern matching, immutable data structures and new idioms your programs can not only become faster but more understandable and maintainable. This talk will take a look at what’s great, what you might miss and augment it with production experience and advice.
Elixir & Phoenix – fast, concurrent and explicitTobias Pfeiffer
Elixir and Phoenix are known for their speed, but that’s far from their only benefit. Elixir isn’t just a fast Ruby and Phoenix isn’t just Rails for Elixir. Through pattern matching, immutable data structures and new idioms your programs can not only become faster but more understandable and maintainable. This talk will take a look at what’s great, what you might miss and augment it with production experience and advice.
Python an-intro youtube-livestream-day2MAHALAKSHMI P
Python an Introduction to List and Strings in English. This presentation has been prepared to take the class in live youtube stream https://youtu.be/-yrO0bOBwsY
The document discusses using Python for ethical hacking and penetration testing. It provides reasons for using Python such as its ease of use, readable syntax, rich libraries, and existing tools. It then covers various Python libraries and frameworks used for tasks like reconnaissance, scanning, exploitation, and packet manipulation. Specific topics covered include file I/O, requests, sockets, scapy, and more.
در این جلسه از کلاس در خصوص تاریخچه پایتون و زبان پایتون صحبت شد
PySec101 Fall 2013 J1E1 By Mohammad Reza Kamalifard
Talk about : Python History and Python language Essentials.
جلسه ۱۸۶ تهران لاگ
By: Mohammad reza Kamalifard
این ارائه در خصوص انواع حمله کنندگان آنلاین ، حملات دولت ها حریم شخصی کاربران و راه حل ها آن محصولی از DSME است
http://datasec.ir
ارائه شده توسط: محمد رضا کمالی فرد
This document discusses the history of open source software and the internet from the 1960s to the present. It notes that in the 1970s, software was generally shared as a hobby but some argued developers should be paid. The first UNIX operating system source code was released to universities in 1977. The document encourages contributing to open source projects through testing, reporting bugs, answering questions, and participating in communities to avoid working alone.
This document introduces the Flask micro web framework. It discusses that Flask provides URL routing, request and response objects, template engines and other features for web development. Flask is simple and extensible, using Werkzeug and Jinja2. It does not include an ORM or form validation, but supports extensions. The document provides examples of basic routing, using request objects, templates and the development server. It also discusses using SQLAlchemy, WTForms and common patterns like MVC with Flask projects.
در این جلسه از کلاس به معرفی ساختار های داده ای در زبان پایتون و معرفی رشته ها و اعداد میپردازیم
PySec101 Fall 2013 J2E1 By Mohammad Reza Kamalifard
Talk About
Python Data Structures, Strings, Numbers,...
The document provides information on arrays and hashes in Ruby. It discusses that arrays are ordered lists that can contain objects, and hashes are collections of key-value pairs. It then provides examples of creating, accessing, and modifying arrays and hashes. It also discusses various methods for iterating over arrays and hashes, such as each, collect, and each_pair.
This document discusses building an inverted index to search text documents. It shows how to tokenize documents into words, build a postings list to map words to the documents that contain them, and use the postings list to search for words in documents. It also discusses additional enhancements like handling punctuation, stemming, stop words, and storing more metadata with postings.
Functional programming languages promise to be easier to test and easier to debug. However, when learning the functional way we often try to translate our current techniques to another language. This is usually not easy and the end result is far from those promises we've heard. Early frustrations might even discourage from further learning.
In this talk I will show you two very simple patterns:
- Designing code around single data structure
- Dealing with impure parts of program like DBs, external services or IO
This should give beginners jump start for their first toy projects and further exploration.
This document provides an overview of lists in Python. It defines lists as ordered, mutable sequences that can contain elements of different data types. Key features covered include: lists allow duplicates, are indexed and sliced, can be modified via assignment, support common operations like membership testing and iteration. Examples are provided for list construction, accessing/replacing items by index, slicing subsets, checking if an item exists, and looping through lists.
This document provides a 5 minute summary of key Python concepts including variables, data types, conditionals, loops, functions, classes and modules. It demonstrates how to define and use integers, floats, strings, booleans, lists, tuples, dictionaries and sets. It also shows the syntax for if/else statements, for/while loops, functions, lambda functions, classes and importing/using modules in Python.
This document provides an introduction to the Elixir programming language. It discusses what Elixir is, how to get started with installation and configuration of Elixir and Erlang, basic and compound data types in Elixir, functions and modules, and higher-order functions and comprehensions. Key topics covered include installing Elixir using ASDF, basic data types like integers, floats, atoms, and more, functions and anonymous functions, modules, and Enum functions like map, reduce, and comprehensions.
PromptWorks Talk Tuesdays: Ray Zane 1/17/17 "Elixir Is Cool"PromptWorks
The document shows examples of pattern matching, case expressions, macros, and queries in Elixir. It demonstrates matching on different data types like lists, maps, tuples, and structs. It also shows examples of macros, case expressions, queries, and defining functions with pattern matching.
This SQL stored procedure performs a multi-step personnel search based on various criteria. It begins with an initial standard search, then applies additional filters for user tags, available dates, contracts, text searches, certification requirements, and personnel statuses to refine the results into a final output table. Temporary tables and dynamic SQL statements are used to sequentially apply each filter and move the results to the next stage.
- The document demonstrates various commands for exploring and summarizing data in R such as the iris data set including head(), tail(), str(), class(), summary(), and $-operator.
- The iris data set contains measurement data for 150 flowers across 4 variables and is stored as a data frame object in R.
- Data frames allow storing different data types together and can be explored using commands like summary() which provides summaries tailored to each variable type.
- Matrices can also be used to store multi-dimensional data and various functions like dim(), apply(), and cbind() allow manipulating the dimensions and combining matrices.
The document discusses using the Paco parsing library in Elixir. It shows how to define parsers for literals, sequences, repetitions, alternatives and more. It also demonstrates parsing expressions, references to elements with quantities, and converting terms to parsers via a Parsable protocol.
The document contains code examples demonstrating various Elixir concepts like defining modules and functions, pattern matching, pipes, macros, and more. It shows interactive sessions in IEx testing concepts like strings, binaries, lists, tuples, pattern matching, recursion, comprehensions, and more. Some examples include defining a module to calculate factorials recursively, working with binaries and binary patterns, building a poker hand evaluator, and using quote and unquote in macros.
Elixir & Phoenix – fast, concurrent and explicitTobias Pfeiffer
Elixir and Phoenix are known for their speed, but that’s far from their only benefit. Elixir isn’t just a fast Ruby and Phoenix isn’t just Rails for Elixir. Through pattern matching, immutable data structures and new idioms your programs can not only become faster but more understandable and maintainable. This talk will take a look at what’s great, what you might miss and augment it with production experience and advice.
Elixir & Phoenix – fast, concurrent and explicitTobias Pfeiffer
Elixir and Phoenix are known for their speed, but that’s far from their only benefit. Elixir isn’t just a fast Ruby and Phoenix isn’t just Rails for Elixir. Through pattern matching, immutable data structures and new idioms your programs can not only become faster but more understandable and maintainable. This talk will take a look at what’s great, what you might miss and augment it with production experience and advice.
Python an-intro youtube-livestream-day2MAHALAKSHMI P
Python an Introduction to List and Strings in English. This presentation has been prepared to take the class in live youtube stream https://youtu.be/-yrO0bOBwsY
The document discusses using Python for ethical hacking and penetration testing. It provides reasons for using Python such as its ease of use, readable syntax, rich libraries, and existing tools. It then covers various Python libraries and frameworks used for tasks like reconnaissance, scanning, exploitation, and packet manipulation. Specific topics covered include file I/O, requests, sockets, scapy, and more.
در این جلسه از کلاس در خصوص تاریخچه پایتون و زبان پایتون صحبت شد
PySec101 Fall 2013 J1E1 By Mohammad Reza Kamalifard
Talk about : Python History and Python language Essentials.
جلسه ۱۸۶ تهران لاگ
By: Mohammad reza Kamalifard
این ارائه در خصوص انواع حمله کنندگان آنلاین ، حملات دولت ها حریم شخصی کاربران و راه حل ها آن محصولی از DSME است
http://datasec.ir
ارائه شده توسط: محمد رضا کمالی فرد
This document discusses the history of open source software and the internet from the 1960s to the present. It notes that in the 1970s, software was generally shared as a hobby but some argued developers should be paid. The first UNIX operating system source code was released to universities in 1977. The document encourages contributing to open source projects through testing, reporting bugs, answering questions, and participating in communities to avoid working alone.
This document introduces the Flask micro web framework. It discusses that Flask provides URL routing, request and response objects, template engines and other features for web development. Flask is simple and extensible, using Werkzeug and Jinja2. It does not include an ORM or form validation, but supports extensions. The document provides examples of basic routing, using request objects, templates and the development server. It also discusses using SQLAlchemy, WTForms and common patterns like MVC with Flask projects.
در این جلسه از کلاس به معرفی ساختار های داده ای در زبان پایتون و معرفی رشته ها و اعداد میپردازیم
PySec101 Fall 2013 J2E1 By Mohammad Reza Kamalifard
Talk About
Python Data Structures, Strings, Numbers,...
This document provides information about Python data types including tuples, sets, and dictionaries. It defines tuples as immutable lists that can be converted from and to lists using tuple() and list(). It describes sets as unordered collections of unique elements and set operations like union, intersection, and difference. Finally, it discusses dictionaries as unordered collections of key-value pairs that allow looking up values by key. It also covers dictionary methods for accessing items, keys, and values as well as adding, removing, and clearing items.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
With pdf.
I wrote anything.
Python elements lists you can study
This is help you to study the python programing.This is useful for your learning.
Happy bro.
.
This document discusses Python lists and their uses. Lists are a mutable data type that allows storing multiple values in a single variable. Values in a list can be accessed by index and lists can be sliced, concatenated, and modified using built-in methods. Lists are commonly used with for loops to iterate over elements. Strings can be split into lists of substrings using the split() method.
Kickstart your data science journey with this Python cheat sheet that contains code examples for strings, lists, importing libraries and NumPy arrays.
Find more cheat sheets and learn data science with Python at www.datacamp.com.
This document provides an overview of selecting elements from lists and numpy arrays in Python. It demonstrates how to select a single element, slice a range of elements, select elements from nested lists and 2D numpy arrays. Various list and numpy array methods are also described, such as sorting, appending, inserting, deleting and calculating statistics.
The document discusses various topics related to lists in Python including:
- Lists can store multiple items of similar or different types in a single variable.
- List items can be accessed and modified using indexes.
- List slicing allows accessing elements within a specified index range.
- Built-in functions like len(), max(), min() etc. can be used to perform operations on lists.
- List methods allow adding, removing, and modifying elements in lists.
- Lists can be passed as arguments to functions and returned from functions.
A tour of Python: slides from presentation given in 2012.
[Some slides are not properly rendered in SlideShare: the original is still available at http://www.aleksa.org/2015/04/python-presentation_7.html.]
This document provides an overview of the Python programming language. It covers topics such as syntax, types and objects, operators and expressions, functions, classes and object-oriented programming, modules and packages, input/output, and the Python execution environment. It also discusses generators and iterators versus regular functions, namespaces and scopes, and classes in Python.
Lists allow storing and manipulating multiple values in a single variable. A list is a mutable collection that can hold elements of any type, accessed by index. Key characteristics of lists include: using square brackets to define lists; mutable elements that can be added, removed, or modified; built-in functions like len(), min(), max(), and sum(); slicing to extract portions; and splitting strings into lists of substrings. Lists are widely used in Python for tasks like collecting related data, looping through elements, and parsing structured data.
Built-in functions in Python include common math functions like abs() and pow(), type-checking functions like isinstance(), string functions like ord() and format(), container functions like list() and tuple(), and IO functions like open() and print(). Some functions return new values like bin() while others operate iteratively like map() or filter() sequences. Many built-ins help with common programming tasks to make code more concise and Pythonic.
Chapter 3 Built-in Data Structures, Functions, and Files .pptxSovannDoeur
This chapter discusses built-in Python data structures, functions, and file handling. It covers common Python data structures like tuples, lists, dictionaries and sets. It describes how to define and use functions, including scope, returning values, and exceptions. It also explains how to open, read, and write to files in Python and deal with different file encodings.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
This document provides an overview of Python data structures including lists, tuples, dictionaries, and sets. It discusses common list methods like append(), insert(), remove(), and sort(). It provides examples of using lists as stacks and queues. It also covers list comprehensions, the del statement, tuple packing and unpacking, set operations, looping through dictionaries, and comparing sequences.
Similar to جلسه سوم پایتون برای هکر های قانونی دوره مقدماتی پاییز ۹۲ (20)
در این جلسه به بررسی ساختار های شرطی و حلقه ها در پایتون پرداختیم
PySec101 Fall 2013 J4E1 By Mohammad Reza Kamalifard
Talk About:
Statements: Conditional Statements and Loop Statements
This document discusses modular programming in Python for ethical hackers. Modular programming breaks code into separate modules to make programs more readable, reliable, and maintainable. A module in Python is a file containing definitions and statements, and takes its name from the file name minus the .py extension. The document demonstrates creating a calculator module with add and sub functions, and importing and using those functions in a test program. It recommends several references for further reading on Python modules and programming.
در این جلسه به بحث
Namespace
Local and Global variables
پرداختیم
PySec101 Fall 2013 J6E2 By Mohammad Reza Kamalifard
Talk About:
Namespace and Local,Global variables in Python
در این جلسه به بررسی بحث برنامه نویسی شی گرا و کلاس ها در پایتون پرداختیم
PySec101 Fall 2013 J7E1 By Mohammad Reza Kamalifard
Talk About:
Object oriented programming and Classes in Python
This document discusses network programming in Python using sockets. It explains that sockets allow communication across networks and the Python socket module provides an interface to work with sockets. It then describes how to create server and client sockets, including binding, listening, accepting connections, and sending/receiving data. It also covers different socket address families like AF_INET for IPv4 and provides code examples for a basic echo server and handling multiple clients using threads or processes.
The document discusses signals in Python programming. It defines signals as allowing handling of asynchronous events. It provides examples of common signals like SIGINT and SIGKILL. It also demonstrates how to write a signal handler in Python to intercept Ctrl-C keyboard interrupts and print a custom message, showing how signals can be used to prevent programs from terminating normally.
The document discusses multi-threaded programming and queues in Python. It describes how to create and manage threads using the thread and threading modules, including starting new threads and getting information about active threads. It also explains how to use queues to coordinate work between threads, including putting and getting items from the queue and waiting for tasks to complete. An example demonstrates creating worker threads that process tasks from a queue and notify the queue when finished.
The document discusses the subprocess module in Python, which allows Python programs to spawn new processes and connect to their input/output/error pipes. It provides examples of using subprocess.call() to run system commands like ls and ps, and subprocess.check_output() to capture the output of commands. The subprocess module intends to replace older modules for process management like os.system, os.spawn, and popen2.
The document discusses Python classes and object-oriented programming concepts. It defines key terms like class, object, method, and inheritance. It provides examples of creating a basic Employee class with methods and instance variables. It also covers class variables, accessing object attributes, adding/removing attributes, inheritance, and overriding methods in subclasses. The goal is to teach Python language essentials for object-oriented programming.
Forking duplicates a process, creating a child process that is identical to the parent. The fork() call returns 0 in the child process and the child's PID in the parent. This allows the parent and child processes to execute independently with different PIDs. Exec functions like execvp() overlay the parent process with a new program, replacing the current process instead of duplicating it like fork().
This document discusses Python directory navigation and file management. It shows how to use the os module to get the current working directory, list files in a directory, create and remove directories, check if an item is a file or directory, and traverse a directory listing files and their types. Code examples demonstrate os.getcwd(), os.listdir(), os.mkdir(), os.rmdir(), and os.path.isfile() and os.path.isdir() to interact with directories and files in Python.
This document discusses file handling in Python. It covers opening, reading, writing, and closing files using functions like open(), read(), write(), and close(). It demonstrates creating a file, appending to it, and reading it line by line. It also shows renaming and removing files using the os module functions os.rename() and os.remove(). The full list of file access modes like read, write, and append are also described.
This document discusses exception handling in Python. It explains that exceptions are error conditions that disrupt normal program flow. Python allows exceptions to be handled elegantly using try and except blocks. It demonstrates how to handle specific exception types like ZeroDivisionError, and how else and finally clauses work with exception handling. The goal is to provide a simple introduction to exception handling in Python.
This document discusses creating modules in Python. It explains that modules allow for better organization of code by defining classes, functions, and variables that can be imported and used in other files. It provides an example of creating a calculator module with add and sub functions, and shows how that module can be imported and its functions called from another file to perform calculations. It also demonstrates importing specific functions from a module using the from keyword.
The document discusses Python conditional statements, loops, and indentation. It covers if/elif statements, while and for loops, and how they work. It provides examples of using conditional logic and loops to check conditions and iterate over items in Python. Proper indentation is emphasized as important in Python to delimit code blocks.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Level 3 NCEA - NZ: A Nation In the Making 1872 - 1900 SML.pptHenry Hollis
The History of NZ 1870-1900.
Making of a Nation.
From the NZ Wars to Liberals,
Richard Seddon, George Grey,
Social Laboratory, New Zealand,
Confiscations, Kotahitanga, Kingitanga, Parliament, Suffrage, Repudiation, Economic Change, Agriculture, Gold Mining, Timber, Flax, Sheep, Dairying,
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Pengantar Penggunaan Flutter - Dart programming language1.pptx
جلسه سوم پایتون برای هکر های قانونی دوره مقدماتی پاییز ۹۲
1. Python for ethical hackers
Mohammad reza Kamalifard
kamalifard@datasec.ir
2. Python language essentials
Module 1:
Introduction to Python and Setting up an Environment for Programing
Part 3 :
Lists,Tuple, Sets, Dictionaries
3. Lists
• Collection of objects which can be heterogeneous
• Lists are like Arrays in C/C++ and Java, but Python lists are by far
more flexible than classical arrays.
>>> my_list = ['English', 'Farsi', 'Arabic', 'German',]
>>> my_list[0]
'English'
>>> my_list[1]
'Farsi'
>>> my_list[-1]
'German'
>>> my_list[2:3]
['Arabic']
>>> my_list[::-1]
['German', 'Arabic', 'Farsi', 'English']
8. Tuples
• Tuples are similar to list but immutable
• Can Convert from list to tuple and vice versa
• tuple(list)
• list(tuple)
>>>my_tuple = ('reza', 1362, 22, 'aban')
>>>my_tuple
('reza', 1362, 22, 'aban')
>>> my_tuple[2]
22
>>> my_tuple[2] = 14
Traceback (most recent call last):
File "<pyshell#7>", line 1, in <module>
my_tuple[2] = 14
TypeError: 'tuple' object does not support item assignment
>>>
10. Sets
• Unordered collection of unique objects
• List to set : b = set(a)
• Set to list : a = list(b)
• Set Operations
• Union: a | b
• Intersection: a & b
• Difference: a - b
13. Dictionaries
• Unordered key-value pairs
• Keys are unique and immutable objects
• Value can change
• Check if a given key is present
• dict.has_key(key)
• key in dict
{ 'key' : 'value' }
>>>my_dic1 = {}
>>>my_dic1['name'] = 'reza'
{'name': 'reza'}
>>> my_dic2 = {'name' : 'reza', 'age' : 23}
>>> my_dic2
{'age': 23, 'name': 'reza'}
14. Dictionaries
>>> user = {'name': 'reza', 'age': 23, 'from': 'Iran'}
>>> user
{'age': 23, 'from': 'Iran', 'name': 'reza'}
>>>
>>> user.has_key('name')
True
>>> user.has_key('hobby')
False
>>> 'name' in user
True
>>> 'Iran' in user
False
15. Dictionaries
• Get tuple of items : dict.items()
• Get list of keys : dict.keys()
• Get list of values : dict.values()
• Get a particular item : dict.get(key)
• Item deletion:
• All item : dict.clear()
• one item: del dict[key]
20. help()
• Help on built-in function replace:
• help(name.replace)
replace(...)
S.replace(old, new[, count]) -> string
Return a copy of string S with all occurrences of substring
old replaced by new. If the optional argument count is
given, only the first count occurrences are replaced.
(END)
21. References
SPSE securitytube training by Vivek Ramachandran
SANS Python for Pentesters (SEC573)
Violent python
Security Power Tools
python-course.eu
----------------------------http://www.tutorialspoint.com/python/python_lists.htm
http://www.tutorialspoint.com/python/python_tuples.htm
http://www.tutorialspoint.com/python/python_dictionary.htm
http://www.python-course.eu/sequential_data_types.php
http://www.python-course.eu/sets_frozensets.php
22. This work is licensed under the Creative Commons Attribution-NoDerivs 3.0 Unported License.
To view a copy of this license, visit
http://creativecommons.org/licenses/by-nd/3.0/
Copyright 2013 Mohammad Reza Kamalifard
All rights reserved.
Go to Kamalifard.ir/pysec101 to Download Slides and Course martials .