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Once you've sorted and filtered the flight data, you can see all those flights in a browser. Clicking on 'Show first flights in browser' will create a web page that will display those flights using Google Maps and then launch your browser to view that file.
JM : I had to reduce the number of rows of the table like this:. Keith,Thanks for sharing this. Jeff Smith : Below is an online demo using CloudTk. It is a It is run under a user account in the Container. For any individual flight, if you click its '? You can click on the location button to show that flight on Google Maps. For all flights, you can search, sort and filter the data in various ways. For example, you can:. Once you've sorted and filtered the flight data, you can see all those flights in a browser.
Clicking on 'Show first flights in browser' will create a web page that will display those flights using Google Maps and then launch your browser to view that file. JM : I had to reduce the number of rows of the table like this:. We will cover conditionals, loops, templates, variables, Ansible Vault, and roles.
It will also cover the basics of writing custom modules. Chapter 6, Network Security with Python, introduces several Python tools to help you secure your network.
It will discuss using Scapy for security testing, using Ansible to quickly implement access lists, and using Python for network forensic analysis. Chapter 7,Network Monitoring with Python — Part 1, covers monitoring the network using various tools. Matplotlib and Pygal examples will be shown for graphing the results. The chapter will end with a Cacti example using a Python script as an input source. Chapter 8, Network Monitoring with Python — Part 2, covers more network monitoring tools.
We will move to use examples with push-based network monitoring using Netflow and other technologies. We will use Python to decode flow packets and ntop to visualize the results. An overview of Elasticsearch and how it can be used for network monitoring will also be covered.
The network API offers benefits such as abstracting the requester from network details, consolidating and customizing operations, and providing better security by limiting the exposure of available operations.
Chapter 11,Working with Git, we will illustrate how we can leverage Git for collaboration and code version control. Practical examples of using Git for network operations will be used in this chapter. Chapter 12,Continuous Integration with Jenkins, uses Jenkins to automatically create operations pipelines that can save us time and increase reliability.
Chapter 13,Test-Driven Development for Networks, explains how to use Python's unittest and PyTest to create simple tests to verify our code.
We will also see examples of writing tests for our network to verify reachability,. We will also see how we can integrate the tests into continuous integration tools, such as Jenkins. Most of the chapters can be read in any order, with the exceptions of chapters 4 and 5, which should be read in sequence. Besides the basic software and hardware tools introduced at the beginning of the book, new tools relevant to each of the chapters will be introduced.
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Once you have read and used this book, why not leave a review on the site that you purchased it from? Potential readers can then see and use your unbiased opinion to make purchase decisions, we at Packt can understand what you think about our products, and our authors can see your feedback on their book. Thank you! When I first started working as a network engineer 18 years ago, at the turn of the millennium, the role was distinctly different than other technical roles. Network engineers mainly possessed domain-specific knowledge to manage and operate local and wide area networks, while occasionally crossing over to systems administration, but there was no expectation to write code or understand programming concepts.
This is no longer the case. Over the years, the DevOps and Software- Defined Networking SDN movement, among other factors, have significantly blurred the lines between network engineers, systems engineers, and developers. The fact that you have picked up this book suggests that you might already be an adopter of network DevOps, or maybe you are considering going down that path.
Maybe you have been working as a network engineer for years, just as I was, and want to know what the buzz around the Python programming language is about.
Or you might already be fluent in Python but wonder what its applications are in network engineering. If you fall into any of these camps, or are simply just curious about Python in the network engineering field, I believe this book is for you:.
The intersection between Python and network engineering. Many books that dive into the topics of network engineering and Python have already been written.
I do not intend to repeat their efforts with this book. Instead, this book assumes that you have some hands-on experience of managing networks, as well as a basic understanding of network protocols and the Python language. You do not need to be an expert in Python or network engineering, but should find that the concepts in this chapter form a general review.
The rest of the chapter should set the level of expectation of the prior knowledge required to get the most out of this book. If you want to brush up on the contents of this chapter, there are lots of free or low-cost resources to bring you up to speed.
This chapter will pay a very quick visit to the relevant networking topics. From my experience working in the field, a typical network engineer or developer might not remember the exact TCP state machine to accomplish their daily tasks I know I don't , but they would be familiar with the basics of the OSI model, the TCP and UDP operations, different IP headers fields, and other fundamental concepts.
We will also look at a high-level review of the Python language; just enough for those readers who do not code in Python on a daily basis to have ground to walk on for the rest of the book. Of course, the information presented in this chapter is not exhaustive; please do check out the references for. This seemingly easy question might receive different answers depending on your background. The internet means different things to different people; the young, the old, students, teachers, business people, poets, could all give different answers to the question.
To a network engineer, the internet is a global computer network consisting of a web of inter-networks connecting large and small networks together. In other words, it is a network of networks without a centralized owner. Take your home network as an example. It might consist of a home Ethernet switch and a wireless access point connecting your smartphone, tablet, computers, and TV together for the devices to communicate with each other.
When your home network needs to communicate with the outside world, it passes information from your LAN to a larger network, often appropriately named the Internet Service Provider ISP. Your ISP often consists of edge nodes that aggregate the traffic to their core network. The core network's function is to interconnect these edge networks via a higher speed network. The return path from your destination to your home computer, tablet, or smartphone may or may not follow the same path through all of these networks back to your device, while the source and destination remain the same.
In today's world, a host can be a traditional computer, or can be your smartphone, tablet, or TV. With the rise of the Internet of Things IoT , the broad definition of a host can be expanded to include an IP camera, TV set-top boxes, and the ever-increasing type of sensors that we use in agriculture, farming, automobiles, and more.
With the explosion of the number of hosts connected to the internet, all of them need to be addressed, routed, and managed. The demand for proper networking has never been greater. Most of the time when we are on the internet, we make requests for services. This could be viewing a web page, sending or receiving emails, transferring files, and so on. These services are provided by servers. As the name implies, servers provide services to multiple nodes and generally have higher levels of hardware specification because of this.
In a way, servers are special super-nodes on the network that provide additional capabilities to its peers. We will look at servers later on in the client-server model section.
If you think of servers and hosts as cities and towns, the network components are the roads and highways that connect them together. In fact, the term information superhighway comes to mind when describing the network components that transmit the ever increasing bits and bytes across the globe.
In the OSI model that we will look at in a bit, these network components are layer one to three devices. They are layer two and three routers and switches that direct traffic, as well as layer one transports such as fiber optic cables, coaxial cables, twisted copper pairs, and some DWDM equipment, to name a few. Because of the higher hardware capacity that servers demand, they are often put together in a central location, so they can be managed more efficiently.
We often refer to these locations as data centers. These services translate into file and mail servers, database servers, and web servers. Unlike user computers, these are generally high-end computers that require a lot of power, cooling, and network connections. A byproduct of the hardware is also the amount of noise they make.
They are generally placed in a central location, called the Main Distribution Frame MDF , in the enterprise to provide the necessary power feed, power redundancy, cooling, and network connectivity.
To connect to the MDF, the user's traffic is generally aggregated at a location closer to the user, which is sometimes called the Intermediate Distribution Frame IDF , before they are bundled up and connected to the MDF. If the enterprise consists of several buildings, further aggregation can be done by combining the buildings' traffic before connecting them to the enterprise data center.
Enterprise data centers generally follow the network design of three layers. These layers are access, distribution, and a core. The access layer is analogous to the ports each user connects to, the IDF can be thought of as the distribution layer, while the core layer consists of the connection to the MDF and the enterprise data centers. This is, of course, a generalization of enterprise networks, as some of them will not follow the same model. Because of the number of servers they house, they generally demand a much, much higher capacity for power, cooling, network speed, and feed than any enterprise data center.
Even after working on cloud provider data centers for many years, every time I visit a cloud provider data center, I am still amazed at the scale of them. In fact, cloud data centers are so big and power-hungry that they are typically built close to power plants where they can get the cheapest power rate, without losing too much efficiency during the transportation of the power. Their cooling needs are so great, some are forced to be creative about where the data center is built, building in a generally cold climate just so they can just open the doors and windows to keep the server running at a safe temperature when needed.
Any search engine can give you some of the astounding numbers when it comes to the science of building and managing cloud data centers for the likes of Amazon, Microsoft, Google, and Facebook:. At the cloud provider scale, the services that they need to provide are generally not cost efficient or able to feasibly be housed in a single server. They are spread between a fleet of servers, sometimes across many different racks, to provide redundancy and flexibility for service owners.
The latency and redundancy requirements put a tremendous amount of pressure on the network. The number of interconnections equates to an explosive growth of network equipment; this translates into the number of times this network equipment needs to be racked, provisioned, and managed.
A typical network design would be a multi-staged, CLOS network:. In a way, cloud data centers are where network automation becomes a necessity for speed and reliability. If we follow the traditional way of managing network devices via a Terminal and command-line interface, the number of engineering hours required would not allow the service to be available in a reasonable amount of time.
This is not to mention that human repetition is error-prone, inefficient, and a terrible waste of engineering talent. Cloud data centers are where I started my path of network automation with Python a number of years ago, and I've never looked back since. All the connections from clients around the world can be routed back to the data center servers providing the service, and we can call it a day, right?
The answer, of course, depends on the use case. The biggest limitation in routing the request and session all the way back from the client to a large data center is the latency introduced in the transport.
In other words, large latency is where the network becomes a bottleneck. The latency number would never be zero: even as fast as light can travel in a vacuum, it still takes time for physical transportation. In the real world, latency would be much higher than light in a vacuum when the packet is traversing through multiple networks, and sometimes through an undersea cable, slow satellite links, 3G or 4G cellular links, or Wi-Fi connections.
The solution? Reduce the number of networks the end user traverses through. Be as closely connected to the user as possible at the edge where the user enters your network and place enough resources at the edge location to serve the request.
Let's take a minute and imagine that you are building the next generation of video streaming service. In order to increase customer satisfaction with smooth streaming, you would want to place the video server as close to the customer as possible, either inside or very near to the customer's ISP. Also, the upstream of the video server farm would not just be connected to one or two ISPs, but all the ISPs that I can connect to to reduce the hop count. All the connections would be with as much bandwidth as needed to decrease latency during peak hours.
This need gave rise to the peering exchange's edge data centers of big ISP and content providers. Even when the number of network devices is not as high as cloud data centers, they too can benefit from network automation in terms of the increased reliability, security, and visibility network automation brings. The model is a conceptional model that componentizes the telecommunication functions into different layers.
The model defines seven layers, and each layer sits independently on top of another one, as long as they follow defined structures and characteristics. For example, in the network layer, IP, can sit on top of the different types of data link layers, such as Ethernet or frame relay.
The OSI reference model is a good way to normalize different and diverse technologies into a set of common language that people can agree on.
This greatly reduces the scope for parties working on individual layers and allows them to look at specific tasks in depth without worrying too much about compatibility:. It is widely accepted and commonly referred to when introducing a new topic in telecommunication. Around the same time period of the OSI model development, the internet was taking shape.
This is somewhat similar to the OSI model in the sense that they divide end-to-end data communication into abstraction layers. What is different is the model combines layers 5 to 7 in the OSI model in the Application layer, while the Physical and Data link layers are combined in the Link layer:. We will specify the OSI model when needed, such as when we are discussing the web framework in upcoming chapters.
Of course, by now, we all know that not all nodes are created equal. Even in its DARPA-net days, there were workstation nodes, and there were nodes with the purpose of providing content to other nodes. These server nodes typically have higher hardware specifications and are managed more closely by engineers. Since these nodes provide resources and services to others, they are typically referred to as servers.
Servers typically sit idle, waiting for clients to initiate requests for their resources. This model of distributed resources that are asked for by the client is referred to as the client-server model.
Why is this important? If you think about it for a minute, the importance of networking is highlighted by this client-server model. Without it, there is really not a lot of need for network interconnections. It is the need to transfer bits and bytes from client to server that shines a light on the importance of network engineering. Of course, we are all aware of how the biggest network of them all, the internet, has been transforming the lives of all of us and continuing to do so.
How, you asked, can each node determine the time, speed, source, and destination every time they need to talk to each other? This brings us to network protocols. These proprietary protocol suites generally have analogous layers to the OSI reference model and follow the client-server communication method. They generally work great in Local Area Networks LAN that are closed, without the need to communicate with the outside world.
When traffic does need to move beyond the local LAN, typically, an internet working device, such as a router, is used to translate from one protocol to another. An example would be a router connecting an AppleTalk network to an IP-based network.
The translation is usually not perfect, but since most of the communication happens within the LAN in the early days, it is okay. However, as the need for inter-network communication rises beyond the LAN, the need for standardizing the network protocol suites becomes greater. The proprietary protocols eventually gave way to the standardized protocol suites of TCP, UDP, and IP, which greatly enhanced the ability of one network to talk to another. The internet, the greatest network of them all, relies on these protocols to function properly.
In the next few sections, we will take a look at each of the protocol suites. If you have opened a web page or have sent an email, you have come across the TCP protocol. The protocol sits at layer 4 of the OSI model, and it is responsible for delivering the data segment between two nodes in a reliable and error-checked manner. The TCP consists of a bit header consisting of, among others, source and destination ports, a sequence number, an acknowledgment number, control flags, and a checksum:.
The server in the client-server model typically listens on one of these well-known ports in order to receive communication requests from the client. The TCP connection is managed by the operating system by the socket that represents the local endpoint for connection.
The protocol operation consists of a state machine, where the machine needs to keep track of when it is listening for an incoming connection, during the communication session, as well as releasing resources once the connection is closed.
The fact that the operation guarantees delivery is often referred to TCP as a connection-oriented protocol. The acknowledgment is used to keep track of subsequent segments in the conversation. As many of us who have troubleshot a TCP connection can tell you, the operation can get quite complex.
One can certainly appreciate that, most of the time, the operation just happens silently in the background. A whole book could be written about the TCP protocol; in fact, many excellent books have been written on the protocol. Unlike TCP, the header is only bit, which only consists of a source and destination port, length, and checksum.
The lightweight header makes it ideal for applications that prefer faster data delivery without setting up the session between two hosts or needing reliable data delivery.
Perhaps it is hard to imagine with today's fast internet connections, but the extra header made a big difference to the speed of transmission in the early days of X. Although, as important as the speed difference is, not having to maintain various states, such as TCP, also saves computer resources on the two endpoints:. You might now wonder why UDP was ever used at all in the modern age; given the lack of reliable transmission, wouldn't we want all the connections to be reliable and error-free?
If you think about multimedia video streaming or Skype calling, those applications benefit from a lighter header when the application just wants to deliver the datagram as quickly as possible.
When the address you type in on the browser is translated into a computer understandable address, the user will benefit from a lightweight process, since this has to happen before even the first bit of information is delivered to you from your favorite website.
Again, this section does not do justice to the topic of UDP, and the reader is encouraged to explore the topic through various resources if you are is interested in learning more about UDP. IP has the job of addressing and routing between end nodes, among others. The addressing of an IP is probably its most important job. The address space is divided into two parts: the network and the host portion.
The subnet mask is used to indicate which portion in the network address consists of the network and which portion is the host by matching the network portion with a 1 and the host portion with a 0.
Both IPv4 and, later, IPv6 expresses the address in the dotted notation, for example, The subnet mask can either be in a dotted notation The Next Header field in the fixed header section can indicate an extension header to be followed that carries additional information.
The extension headers can include routing and fragment information. As much as the protocol designer would like to move from IPv4 to IPv6, the internet today is still pretty much addressed with IPv4, with some of the service provider networks addressed with IPv6 internally. But it can also mean a translation between IPv4 to IPv6, such as at a carrier edge when they use IPv6 inside of the network that needs to be translated to IPv4 when the packet leaves the network.
Sometimes, NAT6 to 6 is used as well for security reasons. Security is a continuous process that integrates all the aspects of networking, including automation and Python. This book aims to use Python to help you manage the network; security will be addressed as part of the following chapters in the book, such as using SSHv2 over telnet. We will also look at how we can use Python and other tools to gain visibility in the network.
For all communication via the internet, the packet will traverse through various intermediate devices. As mentioned, the intermediate devices consist of routers, switches, optical gears, and various other gears that do not examine beyond the network and transport layer.
In a road trip analogy, you might travel in the United States from the city of San Diego in California to the city of Seattle in Washington. On your road trip, you will stop by many different intermediate spots, such as Los Angeles, San Francisco, and Portland; these can be thought of as the routers and switches between the source and destination.
Why was this important? In a way, this book is about managing and optimizing these intermediate devices. In the age of mega data centers that span the size of multiple American football fields, the need for efficient, agile, reliable, and cost-effective ways to manage the network becomes a major point of competitive advantage for companies.
In future chapters, we will dive into how we can use Python programming to effectively manage a network. But what is Python and why is it the language of choice of many DevOps engineers? Its high-level, built-in data structure, combined with dynamic typing and dynamic binding, makes it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.
Python's simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance. If you are somewhat new to programming, the object-oriented, dynamic semantics mentioned previously probably do not mean much to you. But I think we can all agree that for rapid application development, simple, and easy-to-learn syntax sounds like a good thing.
Python, as an interpreted language, means there is no compilation process required, so the time to write, test, and edit Python programs is greatly reduced. For simple scripts, if your script fails, a print statement is usually all you need to debug what was going on. Using the interpreter also means that Python is easily ported to different types of operating systems, such as Windows and Linux, and a Python program written on one operating system can be used on another.
The object-oriented nature encourages code reuse by breaking a large program into simple reusable objects, as well as other reusable formats with functions, modules, and packages. In fact, all Python files are modules that can be reused or imported into another Python program. This makes it easy to share programs between engineers and encourages code reuse. Python also has a batteries included mantra, which means that for common tasks, you need not download any additional packages.
In order to achieve this without the code being too bloated, a set of standard libraries is installed when you install the Python interpreter. For common tasks such as regular expression, mathematics functions, and JSON decoding, all you need is the import statement, and the interpreter will move those functions into your program. This is what I would consider one of the killer features of the Python language. Lastly, the fact that Python code can start in a relatively small-sized script with a few lines of code and grow into a full production system is very handy for network engineers.
As many of us know, the network typically grows organically without a master plan. A language that can grow with your network in size is invaluable.
If you have ever worked in an environment where you have to switch between working on different vendor platforms, such as Cisco IOS and Juniper Junos, you know how painful it is to switch between syntaxes and usage when trying to achieve the same task.
With Python being flexible enough for large and small programs, there is no such context switching, because it is just Python. For the rest of the chapter, we will take a high-level tour of the Python language for a bit of a refresher.
If you are already familiar with the basics, feel free to quickly scan through it or skip the rest of the chapter. Python 3 was released back in , over 10 years ago, with active development with the most recent release of 3. Unfortunately, Python 3 is not backward compatible with Python 2. At the time of writing the second edition of this book, in the middle of , the Python community has largely moved over to Python 3.
The latest Python 2. Fortunately, both versions can coexist on the same machine. With the 2. This book will use Python 3 for its code examples unless otherwise stated. We will also try to point out the Python 2 and Python 3 differences when applicable. If a particular library or framework is better suited for Python 2, such as Ansible see the following information , it will be pointed out and we will use Python 2 instead.
At the time of writing, Ansible 2. Prior to 2. Given the relatively new supportability, many of the community modules are still yet to migrate to Python 3.
Python programs can be run on Windows, Mac, and Linux. In reality, certain care needs to be taken when you need to ensure cross-platform compatibility, such as taking care of the subtle difference between backslashes in Windows filenames. Since this book is for DevOps, systems, and network engineers, Linux is the preferred platform for the intended audience, especially in production.
The code in this book will be tested on the Linux Ubuntu I will also try my best to make sure the code runs the same on the Windows and the MacOS platform. There are several different implementations of the interpreter by the Python development community, such as IronPython and Jython.
In this book, we will use the most common Python interpreter in use today, CPython. Whenever we mention Python in this book, we are referring to CPython unless otherwise indicated. One way you can use Python is by taking advantage of the interactive prompt. This is useful when you want to quickly test a piece of Python code or concept without writing a whole program. This is typically done by simply typing in the Python keyword: Python 3.
In Python 2, you can omit the parentheses. The interactive mode is one of Python's most useful features. In the interactive shell, you can type any valid statement or sequence of statements and immediately get a result back. I typically use this to explore a feature or library that I am not familiar with. Talk about instant gratification! On Windows, if you do not get a Python shell prompt back, you might not have the program in your system search path.
The latest Windows Python installation program provides a checkbox for adding Python to your system path; make sure that is checked. Or you can add the program in the path manually by going to Environment Settings. A more common way to run the Python program, however, is to save your Python file and run it via the interpreter after. This will save you from typing in the same statements over and over again like you have to do in the interactive shell. Python files are just regular text files that are typically saved with the.
The character can be used to specify comments that will not be executed by the interpreter. The following file, helloworld. None: The Null object Numerics: int, long, float, complex, and bool the subclass of int with a True or False value Sequences: str, list, tuple, and range Mappings: dict Sets: set and frozenset. The None type is returned in functions that do not explicitly return anything.
The None type is also used in function arguments to error out if the caller does not pass in an actual value. With the exception of Booleans, the numeric types of int, long, float, and complex are all signed, meaning they can be positive or negative.
A Boolean is a subclass of the integer, which can be one of two values: 1 for True, and 0 for False. The rest of the numeric types are differentiated by how precisely they can represent the number; for example, int are whole numbers with a limited range while long are whole numbers with unlimited range. Floats are numbers using the double- precision representation bit on the machine.
In this and the next few sections, we will use the interactive interpreter to illustrate the different types. Please feel free to type along on your own computer. Sometimes it surprises people that string is actually a sequence type. But if you look closely, strings are a series of characters put together. Strings are enclosed by either single, double, or triple quotes.
The other two commonly used sequence types are lists and tuples. Lists are sequences of arbitrary objects. Lists can be created by enclosing objects in square brackets. Just like strings, lists are indexed by non-zero integers that start at zero. Tuples are similar to lists, created by enclosing values in parentheses. Like lists, the values in the tuple are retrieved by referencing its index number. Therefore, the index of 1 is actually the second element in the sequence.
There are also common functions that can be applied to sequence types, such as checking the number of elements and the minimum and maximum values:. It will come as no surprise that there are various methods that apply only to strings. It is worth noting that these methods do not modify the underlying string data itself and always return a new string. Here are some of the common methods for a list. This list is a very useful structure in terms of putting multiple items together and iterating through them one at a time.
For example, we can make a list of data center spine switches and apply the same access list to all of them by iterating through them one by one. Since a list's value can be modified after creation unlike tuples , we can also expand and contrast the existing list as we move along the program:. The dictionary is what I think of as a poor man's database because it contains objects that can be indexed by keys.
This is often referred to as the associated array or hashing table in other languages. If you have used any of the dictionary-like objects in other languages, you will know that this is a powerful type, because you can refer to the object with a human- readable key.
This key will make more sense for the poor guy who is trying to maintain and troubleshoot the code. That guy could be you only a few months after you wrote the code and troubleshooting at 2 a. The object in the dictionary value can also be another data type, such as a list.
Unlike lists and tuples, sets are unordered and cannot be indexed by numbers. But there is one character that makes sets standout as useful: the elements of a set are never duplicated.
Imagine you have a list of IPs that you need to put in an access list of. The only problem in this list of IPs is that they are full of duplicates. Now, think about how many lines of code you would use to loop through the list of IPs to sort out unique items, one at a time.
However, the built-in set type would allow you to eliminate the duplicate entries with just one line of code. To be honest, I do not use set that much, but when I need it, I am always very thankful it exists. There are also comparison operators. As one would expect, the format of the conditional statement is as follows: if expression: do something elif expression: do something if the expression meets elif expression: do something if the expression meets The while loop will continue to execute until the condition is false, so be careful with this one if you don't want to continue to execute and crash your process : while expression: do something.
The for loop works with any object that supports iteration; this means all the built-in sequence types, such as lists, tuples, and strings, can be used in a for loop. The letter i in the following for loop is an iterating variable, so you can typically pick something that makes sense within the context of your code: for i in sequence: do something.
You can also make your own object that supports the iterator protocol and be able to use the for loop for this object. This practice allows for better modularity, is easier to maintain, and allows for code reuse.
factual_coco/vocab_aligned at main · xieyxclack/factual_coco · GitHub.
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Get in touch with us at service packtpub. At www. He has worked on and helped managed some of the largest networks /28003.txt the industry while working at Amazon AWS, Microsoft Azure, and other companies.
Eric is passionate about network automation, Python, and helping companies build better security postures. Eric is the author of several books and zoom para reunião download classes on networking with Python and network security. He is the proud inventor of two patents in IP telephony.
Eric shares his deep interest in technology through zoom para reunião download books, classes, and his blog, and contributes to some of the popular Python open source projects.
I would like zoom not on laptop windows - zoom sound not on laptop 10 thank the open source and Python community members for generously sharing their knowledge and code with the public. Without their contribution, many of the projects referenced in this book would not have been possible. To my wife and best friend, Joanna, I won the lottery the day I met you.
To my two girls, Mikaelyn and Esmie, you make me so proud, I love you both dearly. His daily work includes working with orchestration tools по ссылке as Ansible to manage network devices. He's a self-taught programmer with zoom para reuni├úo download primary focus on Python.
We have worked with thousands of developers and tech professionals, just like you, to help them share their перейти with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea. Packt is searching for authors like you Preface Who this book is for. What this book covers To get the most out of this book Download the example code files.
Conventions used Get in touch Reviews. IP routing concepts Python language overview Python versions. Running a Python program Python built-in types The None type. Our first Paramiko program More Paramiko features Paramiko for servers.
Putting things together for Paramiko Looking ahead Downsides of Pexpect and Paramiko compared to other tools Idempotent network device interaction. A more declarative framework A quick Ansible example The control node installation. Lab setup Your first Ansible playbook The public key authorization. Our first playbook The advantages of Ansible Agentless. Zoom para reunião download with Jinja2 Ansible networking modules Local connections and facts.
Provider arguments The Ansible Cisco example Ansible 2. Looping over dictionaries Templates Zoom para reunião download Jinja2 template. The Jinja2 conditional Group and host variables Group variables. Ansible roles Writing your own custom module The first custom module. The lab setup Python Scapy Installing Scapy. Scapy resources Access lists Implementing access lists with Ansible.
Additional Matplotlib resources Pygal Installation. Additional Pygal resources Python for Cacti Installation. AWS network overview Virtual private cloud Route tables and route targets. Test-Driven Development for Networks Test-driven development overview Test definitions Topology as code Python's unittest module More on Python testing pytest examples Writing tests for networking Testing for reachability. Testing for Ansible Pytest in Jenkins Jenkins integration.
We are no doubt experiencing a similar time with the rapid changes zoom para reunião download the fields of network engineering. As software development becomes more integrated into all aspects of networking, the traditional command-line interface and vertically integrated network stack methods are no longer the best ways to manage today's networks. For network engineers, the changes we are seeing are full of excitement and opportunities and yet challenging, particularly for those who need to quickly adapt and keep up.
This book has been written to help ease the transition for networking professionals by providing a practical guide that addresses how to evolve from a traditional platform to one built on software-driven practices.
In this book, we use Python as the programming language of choice to master network engineering tasks. Python is an easy-to-learn, high-level programming language that can effectively complement network engineers' creativity and problem-solving skills to streamline daily operations.
Python zoom para reunião download becoming an integral part of many large-scale networks, and through this book, I hope to share with you the lessons I've learned. Since the publication of the first edition, I have been able to have interesting and meaningful conversations with many of the readers of the book.
I am humbled by the success of the first edition of the book and took to the heart of the перейти I was given. In the second edition, I have tried to make the examples and technologies more relevant.
I sincerely hope the new addition is useful to you. A time of change presents great opportunities for technological advancement. The concepts and tools in this book have helped me tremendously in my career, and I hope they can do the same for you. Basic knowledge of networking and Python is recommended. The chapter will review the basics of Python languages such as types, operators, loops, functions, and packages. Chapter 2,Low-Level Network Device Interactions, uses practical examples to illustrate how to use Python to execute commands on a network device.
It will also discuss the challenges приведу ссылку having a CLI-only interface zoom para reuni├úo download automation. The chapter will use the Pexpect and Paramiko libraries for the examples. It also illustrates tools that allow abstraction больше информации low-level tasks while focusing on the intent of the network engineers.
Ansible moves one step further from APIs and focuses on declarative task intent. In this chapter, we will cover the advantages of using Ansible, its high-level architecture, and see some practical examples of Ansible with Cisco, Juniper, and Arista devices. Chapter 5,The Python Automation Framework — Beyond Basics, builds on the knowledge in the previous chapter and covers the more advanced Ansible topics.
We will cover conditionals, loops, templates, variables, Ansible Vault, and roles. It will also cover the basics of writing custom modules. Нажмите чтобы перейти 6, Network Security with Python, introduces several Python tools to help you secure your network. It will discuss using Scapy for security testing, using Ansible to quickly implement access lists, and using Python for network forensic analysis.
Chapter 7,Network Monitoring with Zoom para reuni├úo download — Part 1, covers monitoring the network using various tools. Matplotlib and Pygal examples will be shown for graphing the results.
The chapter will end with a Cacti example using a Python script as an input source. Chapter 8, Network Monitoring with Python — Part 2, covers more network monitoring tools. We will move to use examples with push-based network monitoring using Netflow and other technologies. We will use Python to decode flow packets and ntop to zoom para reuni├úo download the results. An overview of Elasticsearch and how it can be used for network monitoring will also be covered. The network API offers benefits such as abstracting the requester from network details, consolidating and customizing operations, and providing better security by limiting the exposure of available operations.
Chapter 11,Working with Git, we will illustrate how we can leverage Git for collaboration and code version control. Practical examples of using Git for network zoom para reunião download will be used in this chapter. Chapter 12,Continuous Integration with Jenkins, uses Jenkins to automatically create operations pipelines that can save us time and increase reliability. Chapter 13,Test-Driven Development for Networks, explains how to use Python's unittest and PyTest to create simple tests to verify our code.
We will also see examples of writing tests for our network to verify reachability. We will also see how we can integrate the tests into continuous integration tools, such as Zoom para reuni├úo download. Most of the chapters can be read in any order, with the перейти of chapters 4 and 5, which should be read in sequence. Besides the basic software and hardware tools introduced at the beginning of the book, new tools relevant to each of the chapters will be introduced.
If you purchased this book elsewhere, you can visit www. Log in or register at www. Enter the name of the book in the Zoom para reunião download box and follow the onscreen instructions. Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:. In case there's an update zoom para reunião download the code, it will be updated on the existing GitHub repository.
Check them out! CodeInText:Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "The auto-config also generated vty access for both telnet and SSH.
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