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Nor will they stick around long if your website is simply too buggy. Make every effort to keep your site running smoothly. Ensure that videos and images are optimized for faster downloads. Fast purge complete! Can we see a reversal from here. Currently at a very favourable RR. Looks good to buy. GNFC chart is looking good. Wait for green candle to form here on support. If this support holds it is looking good to buy. One important difference between Pexpect regular expressions and Python regular expressions is that the Pexpect matching is non-greedy, which means they will match as little as possible when using special characters.
Because Pexpect performs regular expression on a stream, you cannot look ahead, as the child process generating the stream may not be finished. In general, just keep this in mind and be as specific as you can be on the expect match strings. Something is not quite right here. Compare it to the Terminal output before; the output you expect would be hostname iosv iosv-1 show run i hostname hostname iosv-1 iosv Taking a closer look at the expected string will reveal the mistake.
In this case, we were missing the hash sign behind the iosv-1 hostname. Therefore, the child application treated the second part of the return string as the expected string:. You can see a pattern emerging from the usage of Pexpect after a few examples. The user maps out the sequence of interactions between the Pexpect process and the child application. With some Python variables and loops, we can start to construct a useful program that will help us gather information and make changes to network devices.
The nested dictionary allows us to refer to the same device such as iosv-1 with the appropriate IP address and prompt symbol. We can then use those values for the expect method later on in the loop. You can choose to pass the command back to the user using the interact method.
You can get a lot of information about the child. Python 3 uses byte strings by default. You always have to include the username in the session, answering the ssh new key question, and much more mundane tasks. There are many ways to make SSH sessions work, but luckily, Pexpect has a subclass called pxssh, which specializes in setting up SSH connections. The class adds methods for login, log out, and various tricky things to handle the different situations in the ssh login process.
By default, pxssh uses the Shell prompt to synchronize the output. Putting code into a script makes it easier to use in a production environment, as well as easier to share with your colleagues.
Refer to the following code:! Starts the loop for devices for device in devices. The script further expands from our first Pexpect program with the following additional features:. Also, use w for the file mode instead of wb.
Just like the pxssh subclass of Pexpect, Paramiko simplifies the SSHv2 interaction between the host and the remote device. It also provides both client and server operations. Paramiko is the low-level SSH client behind the high-level automation framework Ansible for its network modules. We will cover Ansible in later chapters.
Let's take a look at the Paramiko library. However, there is a hard dependency on the cryptography library. The library provides low-level, C-based encryption algorithms for the SSH protocol. We will show the Paramiko installation of our Ubuntu The following output shows the installation steps, as well as Paramiko successfully imported into the Python interactive prompt. If you are using Python 2, please follow the steps below. If you are using Python 3, please refer the following command-lines for installing the dependencies.
After installation, we will import the library to make sure it is correctly installed:. This is particularly useful on a slower network connection or a busy device.
This command is not required but is recommended depending on your situation. The next line sets the policy that the client should use when the SSH server's hostname; in this case, iosv-1, is not present in either the system host keys or the application's keys.
In our scenario, we will automatically add the key to the application's HostKeys object. The next few lines invoke a new interactive shell from the connection and a repeatable pattern of sending a command and retrieving the output. Finally, we close the connection. What would happen if you did not clear out the received buffer? For consistency of the deterministic output, we will retrieve the output from the buffer each time we execute a command.
We will loop over a list of devices and commands while using Paramiko instead of Pexpect. This will give us a good compare and contrast of the differences between Paramiko and Pexpect. We include a new method to clear the buffer for sending commands, such as terminal length 0 or enable, because we do not need the output for those commands. We simply want to clear the buffer and get to the execution prompt.
The rest of the program should be pretty self-explanatory, similar to what we have seen in this chapter. The last thing I would like to point out is that since this is an interactive program, we place some buffer and wait for the command to be finished on the remote device before retrieving the output: time.
After we clear the buffer, during the time between the execution of commands, we will wait two seconds. This will give the device adequate time to respond if it is busy. In this section, we will take a look at some of the other features of Paramiko. Let's look at an example of how we can use Paramiko to manage servers. We will use key-based authentication for the SSHv2 session. In this example, I used another Ubuntu virtual machine on the same hypervisor as the destination server.
We will generate a public-private key pair for our Paramiko host: ssh-keygen -t rsa. Treat the private key with the same attention as you would private passwords that you do not want to share with anybody else. You can think of the public key as a business card that identifies who you are.
Using the private and public keys, the message will be encrypted by your private key locally and decrypted by the remote host using the public key. We should copy the public key to the remote host. Open up a Terminal window for the remote server, so you can paste in the public key. You are now ready to use Paramiko to manage the remote host. Notice that in the server example, we do not need to create an interactive session to execute multiple commands. You can now turn off password-based authentication in your remote host's SSHv2 configuration for more secure key-based authentication with automation enabled.
Some network devices, such as Cumulus and Vyatta switches, also support key-based authentication. In this last section, let's make the Paramiko program more reusable. There is one downside of our existing script: we need to open up the script every time we want to add or delete a host, or whenever we need to change the commands we want to execute on the remote host.
This is due to the fact that both the host and command information are statically entered inside of the script. Hardcoding the host and command has a higher chance of making mistakes. Besides, if you were to pass on the script to colleagues, they might not feel comfortable working in Python, Paramiko, or Linux.
By making both the host and command files be read in as parameters for the script, we can eliminate some of these concerns. Users and a future you can simply modify these text files when you need to make host or command changes. Instead of hardcoding the commands, we broke the commands into a separate commands. Up to this point, we have been using show commands; in this example, we will make configuration changes.
The device's information is written into a devices. In the script, we made the following changes: with open 'devices. Do a quick check to make sure the change has taken place in both running-config and startup-config: iosv-1 sh run i logging logging buffered iosv-1 sh start i logging logging buffered However, the method we have used feels like somewhat of a workaround for automation.
We attempted to trick the remote devices into thinking they were interacting with a human on the other end. They return data that is ideal to be fitted on a terminal to be interpreted by a human, not by a computer program. The human eye can easily interpret a space, while a computer only sees a return character. We will take a look at a better way in the upcoming chapter. But in this book's context, the term means that when a client makes the same call to a remote device, the result should always be the same.
I believe we can all agree that this is necessary. Imagine a scenario where each time you execute the same script, you get a different result back. I find that scenario very scary. How can you trust your script if that is the case? It would render our automation effort useless because we need to be prepared to handle different returns. Since Pexpect and Paramiko are blasting out a series of commands interactively, the chance of having a non- idempotent interaction is higher.
Going back to the fact that the return results needed to be screen scraped for useful elements, the risk of difference is much higher. Something on the remote end might have changed between the time we wrote the script and the time when the script is executed for the th time. For example, if the vendor makes a screen output change between releases without us updating the script, the script might break. If we need to rely on the script for production, we need the script to be idempotent as much as possible.
Computers are much faster at executing tasks than us human engineers. If we had the same set of operating procedures executed by a human versus a script, the script would finish faster than humans, sometimes without the benefit of having a solid feedback loop between procedures. The internet is full of horror stories of when someone pressed the Enter key and immediately regretted it.
We need to make sure the chances of bad automation scripts screwing things up are as small as possible. We all make mistakes; carefully test your script before any production work and small blast radius are two keys to making sure you can catch your mistake before it comes back and bites you.
Without a way to programmatically communicate and make changes to network devices, there is no automation. We looked at two libraries in Python that allow us to manage devices that were meant to be managed by the CLI. Although useful, it is easy to see how the process can be somewhat fragile. This is mostly due to the fact that the network gears in question were meant to be managed by human beings and not computers. Both of these tools use a persistent session that simulates a user typing in commands as if they are sitting in front of a Terminal.
This works fine up to a point. It is easy enough to send commands over for execution on the device and capture the output. However, when the output becomes more than a few lines of characters, it becomes difficult for a computer program to interpret the output. The returned output from Pexpect and Paramiko is a series of characters meant to be read by a human being.
The structure of the output consists of lines and spaces that are human-friendly but difficult to be understood by computer programs.
In order for our computer programs to automate many of the tasks we want to perform, we need to interpret the returned results and make follow-up actions based on the returned results. When we cannot accurately and predictably interpret the returned results, we cannot execute the next command with confidence.
Luckily, this problem was solved by the internet community. Imagine the difference between a computer and a human being when they are both reading a web page. The human sees words, pictures, and spaces interpreted by the browser; the computer sees raw HTML code, Unicode characters, and binary files.
What happens when a website needs to become a web service for another computer? The same web resources need to accommodate both human clients and other computer programs. Doesn't this problem sound familiar to the one that we presented before? It is important to note that an API is a concept and not a particular technology or framework, according to Wikipedia. In computer programming, an Application Programming Interface API is a set of subroutine definitions, protocols, and tools for building application software.
In general terms, it's a set of clearly defined methods of communication between various software components. A good API makes it easier to develop a computer program by providing all the building blocks, which are then put together by the programmer. In our use case, the set of clearly defined methods of communication would be between our Python program and the destination device. The APIs from our network devices provide a separate interface for the computer programs.
The exact API implementation is vendor specific. Despite the differences, the idea of an API remains the same: it is a separate communication method optimized for other computer programs. In my first job as an intern for a local ISP, wide-eyed and excited, my first assignment was to install a router on a customer's site to turn up their fractional frame relay link remember those?
How would I do that? I asked. I was handed a standard operating procedure for turning up frame relay links. I went to the customer site, blindly typed in the commands, and looked at the green lights flashing, then happily packed my bag and patted myself on the back for a job well done.
As exciting as that first assignment was, I did not fully understand what I was doing. I was simply following instructions without thinking about the implication of the commands I was typing in. How would I troubleshoot something if the light was red instead of green? I think I would have called back to the office and cried for help tears optional. Of course, network engineering is not about typing in commands into a device, but it is about building a way that allows services to be delivered from one point to another with as little friction as possible.
The commands we have to use and the output that we have to interpret are merely means to an end. In other words, we should be focused on our intent for the network. What we want our network to achieve is much more important than the command syntax we use to get the device to do what we want it to do. If we further extract that idea of describing our intent as lines of code, we can potentially describe our whole infrastructure as a particular state.
The infrastructure will be described in lines of code with the necessary software or framework enforcing that state. In my opinion, Intent-Driven Networking is the idea of defining a state that the network should be in and having software code to enforce that state.
As an example, if my goal is to block port 80 from being externally accessible, that is how I should declare it as the intention of the network. The underlying software will be responsible for knowing the syntax of configuring and applying the necessary access-list on the border router to achieve that goal. Of course, Intent-Driven Networking is an idea with no clear answer on the exact implementation. But the idea is simple and clear, I would hereby argue that we should focus as much on the intent of the network and abstract ourselves from the device-level interaction.
In using an API, it is my opinion that it gets us closer to a state of intent-driven networking. In short, because we abstract the layer of a specific command executed on our destination device, we focus on our intent instead of the specific commands. For example, going back to our block port 80 access-list example, we might use access-list and access-group on a Cisco and filter-list on a Juniper.
However, in using an API, our program can start asking the executor for their intent while masking what kind of physical device it is they are talking to.
We can even use a higher-level declarative framework, such as Ansible, which we will cover in Chapter 4, The Python Automation Framework — Ansible Basics. But for now, let's focus on network APIs.
The line break, white spaces, and the first line of the column title are easily distinguished from the human eye. In fact, they are there to help us line up, say, the IP addresses of each interface from line one to line two and three. If we were to parse out that data, here is what I would do in a pseudo-code fashion simplified representation of the code I would write :.
Split each line via the line break. I may or may not need the first line that contains the executed command of show ip interface brief. For now, I don't think I need it. Take out everything on the second line up until the VRF, and save it in a variable as we want to know which VRF the output is showing.
For the rest of the lines, because we do not know how many interfaces there are, we will use a regular expression statement to search if the line starts with possible interfaces, such as lo for loopback and Eth for Ethernet interfaces. We will need to split this line into three sections via space, each consisting of the name of the interface, IP address, and then the interface status.
Whew, that is a lot of work just for something that a human being can tell at a glance! You might be able to optimize the code and the number of lines, but in general this is what we need to do when we need to screen scrap something that is somewhat unstructured. There are many downsides to this method, but some of the bigger problems that I can see are listed as follows:.
Scalability: We spent so much time on painstaking details to parse out the outputs from each command. It is hard to imagine how we can do this for the hundreds of commands that we typically run. Predictability: There is really no guarantee that the output stays the same between different software. If the output is changed ever so slightly, it might just render our hard-earned battle of information gathering useless. Vendor and software lock-in: Perhaps the biggest problem is that once we spend all this time parsing the output for this particular vendor and software version, in this case, Cisco NX-OS, we need to repeat this process for the next vendor that we pick.
I don't know about you, but if I were to evaluate a new vendor, the new vendor is at a severe on-boarding disadvantage if I have to rewrite all the screen scrap code again. Right away, you can see the output is structured and can be mapped directly to the Python dictionary data structure. There is no parsing required—you can simply pick the key and retrieve the value associated with the key. You can also see from the output that there are various metadata in the output, such as the success or failure of the command.
If the command fails, there will be a message telling the sender the reason for the failure. You no longer need to keep track of the command issued, because it is already returned to you in the input field. This type of exchange makes life easier for both vendors and operators. On the vendor side, they can easily transfer configuration and state information. They can add extra fields when the need to expose additional data arises using the same data structure. On the operator side, they can easily ingest the information and.
It is generally agreed on that automation is much needed and a good thing. The questions are usually centered on the format and structure of the automation. As you will see later in this chapter, there are many competing technologies under the umbrella of API. Ultimately, the overall market might decide about the final data format in the future. In the meantime, each of us can form our own opinions and help drive the industry forward. A data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to properties of the real-world entities.
For instance, a data model may specify that the data element representing a car be composed of a number of other elements which, in turn, represent the color and size of the car and define its owner. Data modeling process. When applied to the network, we can apply this concept as an abstract model that describes our network, be it a data center, campus, or global wide area network. If we take a closer look at a physical data center, a layer 2 Ethernet switch can be thought of as a device containing a table of MAC addresses mapped to each port.
Similarly, we can move beyond devices and map the whole data center in a model. We can start with the number of devices in each of the access, distribution, and core layers, how they are connected, and how they should behave in a production environment. For example, if we have a fat-tree network, how many links should each of the spine routers have, how many routes they should contain, and how many next-hops should each of the prefixes have?
These characteristics can be mapped out in a format that can be referenced against the ideal state that we should always check against.
It was first published in RFC in , and has since gained traction among vendors and operators. At the time of writing, the support for YANG has varied greatly from vendors to platforms. The adaptation rate in production is therefore relatively low. However, it is a technology worth keeping an eye out for. In their push for network automation, they have made various in-house developments, product enhancements, partnerships, as well as many external acquisitions.
However, with product lines spanning routers, switches, firewalls, servers unified computing , wireless, the collaboration software and hardware, and analytic software, to name a few, it is hard to know where to start. Since this book focuses on Python and networking, we will scope this section to the main networking products. In particular, we will cover the following:.
Since ACI is a separate product and is licensed with the physical switches for the following ACI examples, I would recommend using the DevNet labs to get an understanding of the tools. If you are one of the lucky engineers who has a private ACI lab that you can use, please feel free to use it for the relevant examples. We will use the similar lab topology as we did in Chapter 2, Low-Level Network Device Interactions, with the exception of one of the devices running nx-osv:.
You may already have some of the packages such pip and git:. We will install this from the GitHub repository so that we can install the latest version:. For our lab, we will turn on both HTTP and the sandbox configuration, as they should be turned off in production: nx-osv-2 config nxapi http port 80 nx-osv-2 config nxapi sandbox. In the last step, we turned it on for learning purposes. It should be turned off in production. Let's launch a web browser and take a look at the various message formats, requests, and responses based on the CLI commands that we are already familiar with:.
The sandbox comes in handy if you are unsure about the supportability of the message format, or if you have. In our first example, we are just going to connect to the Nexus device and print out the capabilities exchanged when the connection was first made:! The connection parameters of the host, port, username, and password are pretty self- explanatory. The device parameter specifies the kind of device the client is connecting to. Hopefully, by the time you read this section, the issue is already fixed.
We will use the same library later on in this book. If you click on it, you will be able to get an automatically converted Python script based on the request library. The following script uses an external Python library named requests. For the show version example, the following Python script is automatically generated for you. I am pasting in the output without any modification:. The output was parsed to include only the software version.
The best part about using this method is that the same overall syntax structure works with both configuration commands as well as show commands. For multiline configuration, you can use the ID field to specify the order of operations.
We can verify the result of the previous configuration script by looking at the running-configuration of the Nexus device:. Let's look into it a little bit more with examples.
YANG, being relatively new, has a spotty supportability across vendors and product lines. For example, if we run the same capability exchange script that we have used before for a Cisco v running IOS-XE, this is what we will see: urn:cisco:params:xml:ns:yang:cisco-virtual-service? Audience intersections beta. Here you will find answers to frequently asked questions and instructions.
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