Pometryis in the Business Intelligence Industry

Pometry

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Time to Ditch Requirements.txt now! Start Using Poetry. Python Poetry Example Have you ever run into an issue where you wrote a program and created a “requirements.txt” file and wrote down all the required packages in the requirements.txt file, but when you tried to move the project from one system to another, your program did not work anymore? Even after installing all the packages from requirements.txt still, it’s not working We will learn about Python Poetry Examples. This is called package dependency issues. Though requirements.txt is used to solve dependencies in some ways, still, it’s not perfect. Sometimes, packages written in requirements.txt become obsolete which is why when you try to install them it throws an error. So how to solve package dependency issues? To solve such type of issue, Poetry came into the picture. Table of Contents What is Poetry? How to Install Poetry Python? Install Poetry using PIP Install Poetry on Windows Install Poetry on Linux Let’s make our life easier with Poetry Python Create a Python project by using Poetry Python What is pyproject.toml in Poetry? [tool.poetry] table in poetry pyproject.toml [tool.poetry.dependencies] section in poetry pyproject.toml [build-system] section in poetry prproject.toml Handling Virtual Environment Using Poetry How to activate Virtual Environment using Poetry How to Delete Virtual Environment Using Poetry Let’s start building the Project Creating the Driver Code main.py Install Packages using Poetry Add Command Install Dev Package using Poetry Add Command Remove Package using Poetry Remove Command How to format code using a Black Python Formatter? What are the poetry lock files? Add Poetry to existing Project. Create pyproject.toml using the existing Requirements.txt file Create Requirements.txt using existing poetry.lock file Poetry command to create Requirements.txt file Download Premium Poetry Cheatsheet for FREE👇 Conclusion What Is Poetry? Poetry is a package dependencies management tool for Python that easily solves all these issues. It’s a bundle with all things ready to go. You don’t need to worry about the virtual environment, tracking down packages, separating dev and required packages, etc. It’s all taken care of by Poetry. Today, most Python developers have started using Poetry. It has become a basic necessity of Python projects. You will soon learn why it’s so important; keep following the tutorial. How to Install Poetry Python? Install Poetry using PIP This is the simplest and easiest method to install poetry, and this method works for Windows, Linux, and MacOS. Make sure you already have pip installed. pip install poetry Install Poetry on Windows This method only works for the Windows operating system. Just open Powershell (Not CMD) and type this command. (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | py - If the above command doesn’t work. then only try this. (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python - Install Poetry on Linux Just run the below command in the terminal, and it will automatically install the poetry. curl -sSL https://install.python-poetry.org | python3 - Now, confirm the installation of poetry by running the command poetry --version Also Read: Docker Commands with example Let’s Make Our Life Easier With Poetry Python Now, that we have successfully installed poetry in our system, you can verify the installation of poetry by running the command . In daily programmers’ lives, we just create a Python file and directly start writing the Python program in it. Though it’s not wrong, it’s not the best way to initialize a Python project. poetry --version You should at least create a folder to save your .py files, a readme.md file and lastly requirements.txt file. Let’s understand all the Poetry commands by creating a small project that utilizes all the poetry commands. The name of our project will be “wifiPwd.” Here, I’m going to create a small Python program that will show the password of saved wifi networks in your system. Full project GitHub Link: Github Create a Python Project By Using Poetry Python Poetry can create a Boilerplate template for your project; you just need to use poetry new the command to create a new project. By using this command, poetry will create all the necessary files required in a project. poetry new wifiPwd This command will create a folder named wifiPwd, and inside the folder, you will see a list of files; we will go through each of them individually. The folder structure looks like this: D:\PROJECTS\WIFIPWD
│   pyproject.toml
│   README.md
│
├───tests
│       __init__.py
│
└───wifipwd
        __init__.py Tip! You can use the “Tree” command to view the folder structure file is an instruction file that contains documentation of Installation, usage, required packages, etc. contains some tests for your project; you can use to add test cases to your project. README.md tests. .py init “pytest” is the heart of your project; inside , you can add all your Python files or codes; the main code lies here**.** wifipwd. .py init wifipwd is a file that manages the dependencies of your project. .pyproject.toml The first file we see is “pyproject.toml” file. Let’s inspect the “pyproject.toml” file What Is pyproject.toml in Poetry? Pyproject.toml is a configuration file made in toml. You can learn more about . It’s a configuration file better than .ini, .cfg, and .json, and it’s easily readable for humans. pyproject.toml file is used to track down all Python dependencies. The content of pyproject.toml file looks like this. toml from here [tool.poetry]
name = "wifipwd"
version = "0.1.0"
description = ""
authors = ["Pratik Pathak <pratikpathak200@gmail.com>"]
readme = "README.md"

[tool.poetry.dependencies]
python = "^3.9"

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" You can see the file is divided into 3 sections encapsulated in []; these sections are known as tables. Let’s go through each section one by one. [tool.poetry] table in poetry pyproject.toml tool.poetry table tells us about the project. It gives a general idea of the project. – name of the project name – version of your project version – quick info about the project description – name of authors who contributed authors – link to the readme.md file readme [tool.poetry.dependencies] section in poetry pyproject.toml This is the most important section pyproject.toml. This section tracks down all the dependencies required by the project. In layman’s terms, this is the replacement of . We will keep an eye on this file and mostly on this section while going through the tutorial. requirements.txt We will observe this section whenever we add or remove the packages. Currently, you can see only one dependency python = “^3.9” which means the Python version starts from 3.9 [build-system] section in poetry prproject.toml This section defines the build tools. This section is used to build the packages. It is utilized by the command. poetry build Handling Virtual Environment Using Poetry The next step is to create a virtual environment for our project. There are multiple ways to create a virtual environment; the most popular ones are “virtualenv” and “venv.” You don’t need to create a Python virtual environment by yourself. virtual environment in Python? Why do we need a This is to manage multiple versions of packages and isolate the project. For a particular type of project, we needed a particular version specific to the package which conflicts with existing updated packages. To solve this, it’s best to create a Isolated Virtual Environment, and install the required packages in it. To create a virtual environment using poetry, use the command: poetry use env python This command will create a virtual environment for you to use and automatically activate it. When you run the command, you will see something like this use env Using virtualenv:
C:\Users\pratik\AppData\Local\pypoetry\Cache\virtualenvs\wifipwd-s1RAI5FV-py3.9 Pro Tip!: In place of “Python,” you can give the path of the Python interpreter. By using this tip, you can create a virtual environment using different versions of Python. Example. poetry use env C:\Users\pratik\AppData\Local\Programs\Python\Python39\python.exe You can use command to list down all the virtual env; you can create multiple that use different Python versions. poetry env list How to Activate Virtual Environment Using Poetry You can easily activate Virtual Environment using the command poetry shell Pro Tip!: If you have not created the virtual environment, the “poetry shell” command will create one for you and activate it. How to Delete Virtual Environment Using Poetry To delete the virtual environment, use the command poetry env remove envName If you don’t know the name of the env, you can run command to get the env name. poetry env list Also Read: Docker Run Command example the ultimate cheatsheet Let’s Start Building the Project Creating the Driver Code main.py Let’s create a Python file named “main.py” in the root folder. The project entry point will be from here. Before writing the code, let’s install all required packages beforehand. We will use “ ” to create an interactive terminal. Let’s install PyInquirer using command. PyInquirer poetry add Install Packages Using Poetry Add Command poetry add pyinquirer This command will fetch the PyPi registry. Download the packages from here, and install them in your system. This will also update the pyproject.toml file; it will add Pyinquirer into dependencies. Now, we need a tool for formatting Python code. We will use the “Black” package for formatting our code. But this is not mandatory for the project, it’s a dev dependency, We want to format the code for us easily, it has no purpose in production which’s why it’s a dev dependency Install Dev Package Using Poetry Add Command poetry add black --group dev This will install “black” on your virtual environment, and poetry will add “black” as a dev dependency in pyproject.toml Remove Package Using Poetry Remove Command poetry remove packageName This will remove the package from the environment as well as from pyproject.toml First thing first, Step 0 of our program will be to run the command. poetry install This will validate the file, and then it will install all the dependencies in the file. pyproject.toml After running “poetry install,” you will see output something like this. Creating virtualenv wifipwd-s1RAI5FV-py3.9 in C:\Users\pratik\AppData\Local\pypoetry\Cache\virtualenvs
Resolving dependencies... (0.1s)

Installing the current project: wifipwd (0.1.0) Did you notice? It says “Installing the current project: wifipwd (0.1.0)”, what does it mean? It means Poetry is treating the whole project as a package. Now, you can use it to import the project functionality directly. import wifipwd The Final pyproject.toml will look something like this – [tool.poetry]
name = "wifipwd"
version = "0.1.0"
description = ""
authors = ["Pratik Pathak <pratikpathak200@gmail.com>"]
readme = "README.md"

[tool.poetry.dependencies]
python = "^3.9"
pyinquirer = "^1.0.3"

[tool.poetry.group.dev.dependencies]
black = "^23.12.1"

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api" Now, let’s go back to main.py file… Here, we have to take input from the user in our example wifi name, and then, we will just show the output. The main.py file will look something like this import subprocess
from PyInquirer import prompt
from wifipwd import wifiPassword

data = (
    subprocess.check_output(["netsh", "wlan", "show", "profiles"])
    .decode("utf-8")
    .split("\n")
)
profiles = [i.split(":")[1][1:-1] for i in data if "All User Profile" in i]

question = [
    {
        "type": "list",
        "name": "wifi",
        "message": "Choose the wifi whose password you want to see",
        "choices": profiles,
    }
]
answer = prompt(question)
wifiName = answer["wifi"]
results = wifiPassword(wifiName)

try:
    print("{:<30}|  \033[92m{:<}\033[00m".format(wifiName, results))
except IndexError:
    print("{:<30}|  {:<}".format(wifiName, "")) Did you notice? We used “from wifipwd import wifiPassword.” We are treating the whole project like a package, so let’s write the “wifiPassword” function. wifiPassword function will be located at “wifipwd > .py.” init Now, we will add wifiPassword() function. Let’s edit “wifipwd > .py.” The final “ .py” will look like init init import subprocess

def wifiPassword(name):
    try:
        results = (
            subprocess.check_output(
                ["netsh", "wlan", "show", "profile", name, "key=clear"]
            )
            .decode("utf-8")
            .split("\n")
        )
    except subprocess.CalledProcessError:
        print("{:<30}|  {:<}".format(name, "ENCODING ERROR"))

    results = [b.split(":")[1][1:-1] for b in results if "Key Content" in b]
    try:
        return results[0]
    except IndexError:
        return "" The Project is almost completed. The last step will be to format the code. We have already installed the `Black` Python package for code formatting. Let’s format our code using black. How to Format Code Using a Black Python Formatter? It’s very easy to format our code using “Black;” just run the below command. black main.py Pro Tip! You can also format the whole folder by providing the folder name for example. black wifipwd You will output something like this All done! ✨ 🍰 ✨
1 file reformatted. Note: If you get any error, make sure you are inside the virtual environment; use “poetry shell” to activate the virtual environment. If it still not working, update the black by using “poetry add black@latest.” Now, to make sure everything is okay and running, run “poetry install” one more time. After making sure everything is working smoothly let’s lock the dependencies using poetry. What Are the Poetry Lock Files? Lock files are like a freezing point; they lock the packages and make sure every developer has exactly the same packages this ensures smooth synchronization between developers. Poetry automatically creates a lock file as soon as you run ; you can also use the below command to create the “poetry.lock” file. poetry install poetry lock Whenever we run the command , poetry first reads the “poetry.lock” file, and then it reads the “pyproject.toml” file. poetry install Add Poetry to Existing Project. You may have some other project that does not use poetry beforehand, and it is dependent on the requirements.txt file. You can add poetry to your project by running the command poetry init It will open an interactive terminal. Just fill out all the details, and you are done. >>poetry init                                                                                                                                  

This command will guide you through creating your pyproject.toml config.

Package name [wifipwd]: 
Version [0.1.0]:  
Description []:  
Author [Pratik Pathak <pratikpathak200@gmail.com>, n to skip]:  
License []:  
Compatible Python versions [^3.12]:  3.9

Would you like to define your main dependencies interactively? (yes/no) [yes] no
Would you like to define your development dependencies interactively? (yes/no) [yes] no
Generated file This will create a pyproject.toml file for you, and you are ready to go 🏃‍♂️. Create pyproject.toml Using the Existing Requirements.txt file If you have an existing requirements.txt file and want to move to poetry, you can easily do it by using the command poetry add `cat requirement.txt` Tip! If you want to add packages as dev dependencies, use the command. poetry add `cat requirement.txt` --group dev Create Requirements.txt Using Existing poetry.lock File You may be wondering why we need the requirements.txt file when we already have poetry.lock/pyproject.toml file. The answer is simple: to make it compatible. When you try to deploy your project online, the platform provider uses the “requirements.txt” file. Poetry command to create Requirements.txt file poetry export --output requirements.txt Note: Make sure you have already installed the “poetry-plugin” package. Run the command “pip install poetry-plugin” to install the package This command will create the requirements.txt file using poetry.lock file. But wait, this is not a normal requirements.txt file. Let’s inspect the poetry-generated requirements.txt file. When you look closely, you will observe that the poetry requirements.txt file contains two more fields, first “python_version” and second some hash value. These values ensure that the same package should get installed when we run pip install -r requirements.txt If you like our project, don’t forget to give a star ⭐ to the repo. Full project GitHub Link: GitHub Conclusion We learned about Poetry using a Python poetry example. We have gone through all the poetry commands one by one. Also, we have seen how to create requirements.txt using poetry. Poetry can be used to manage the dependencies; it’s a stop solution for everything. It also manages a virtual environment. With Poetry, you don’t need any other tool; you no longer have to maintain requirements.txt manually.

Learn Python Poetry and Start Using It Now

Mark Twain's Speeches by Mark Twain, is part of the HackerNoon Books Series. You can jump to any chapter in this book . ON POETRY, VERACITY, AND SUICIDE here ON POETRY, VERACITY, AND SUICIDE ADDRESS AT A DINNER OF THE MANHATTAN DICKENS FELLOWSHIP,
          NEW YORK CITY, FEBRUARY 7, 1906

          This dinner was in commemoration of the ninety-fourth
          anniversary of the birth of Charles Dickens.  On an other
          occasion Mr. Clemens told the same story with variations and a
          different conclusion to the University Settlement Society. I always had taken an interest in young people who wanted to become poets. I remember I was particularly interested in one budding poet when I was a reporter. His name was Butter. One day he came to me and said, disconsolately, that he was going to commit suicide—he was tired of life, not being able to express his thoughts in poetic form. Butter asked me what I thought of the idea. I said I would; that it was a good idea. “You can do me a friendly turn. You go off in a private place and do it there, and I’ll get it all. You do it, and I’ll do as much for you some time.” At first he determined to drown himself. Drowning is so nice and clean, and writes up so well in a newspaper. But things ne’er do go smoothly in weddings, suicides, or courtships. Only there at the edge of the water, where Butter was to end himself, lay a life-preserver—a big round canvas one, which would float after the scrap-iron was soaked out of it. Butter wouldn’t kill himself with the life-preserver in sight, and so I had an idea. I took it to a pawnshop, and [soaked] it for a revolver: The pawnbroker didn’t think much of the exchange, but when I explained the situation he acquiesced. We went up on top of a high building, and this is what happened to the poet: He put the revolver to his forehead and blew a tunnel straight through his head. The tunnel was about the size of your finger. You could look right through it. The job was complete; there was nothing in it. Well, after that that man never could write prose, but he could write poetry. He could write it after he had blown his brains out. There is lots of that talent all over the country, but the trouble is they don’t develop it. I am suffering now from the fact that I, who have told the truth a good many times in my life, have lately received more letters than anybody else urging me to lead a righteous life. I have more friends who want to see me develop on a high level than anybody else. Young John D. Rockefeller, two weeks ago, taught his Bible class all about veracity, and why it was better that everybody should always keep a plentiful supply on hand. Some of the letters I have received suggest that I ought to attend his class and learn, too. Why, I know Mr. Rockefeller, and he is a good fellow. He is competent in many ways to teach a Bible class, but when it comes to veracity he is only thirty-five years old. I’m seventy years old. I have been familiar with veracity twice as long as he. And the story about George Washington and his little hatchet has also been suggested to me in these letters—in a fugitive way, as if I needed some of George Washington and his hatchet in my constitution. Why, dear me, they overlook the real point in that story. The point is not the one that is usually suggested, and you can readily see that. The point is not that George said to his father, “Yes, father, I cut down the cheery-tree; I can’t tell a lie,” but that the little boy—only seven years old—should have his sagacity developed under such circumstances. He was a boy wise beyond his years. His conduct then was a prophecy of later years. Yes, I think he was the most remarkable man the country ever produced-up to my time, anyway. Now then, little George realized that circumstantial evidence was against him. He knew that his father would know from the size of the chips that no full-grown hatchet cut that tree down, and that no man would have haggled it so. He knew that his father would send around the plantation and inquire for a small boy with a hatchet, and he had the wisdom to come out and confess it. Now, the idea that his father was overjoyed when he told little George that he would rather have him cut down, a thousand cheery-trees than tell a lie is all nonsense. What did he really mean? Why, that he was absolutely astonished that he had a son who had the chance to tell a lie and didn’t. I admire old George—if that was his name—for his discernment. He knew when he said that his son couldn’t tell a lie that he was stretching it a good deal. He wouldn’t have to go to John D. Rockefeller’s Bible class to find that out. The way the old George Washington story goes down it doesn’t do anybody any good. It only discourages people who can tell a lie. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Mark Twain (2004). Mark Twain's Speeches. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/3188/pg3188-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

ON POETRY, VERACITY, AND SUICIDE

Mark Twain's Speeches by Mark Twain, is part of the HackerNoon Books Series. You can jump to any chapter in this book . OBITUARY POETRY here OBITUARY POETRY ADDRESS AT THE ACTORS’ FUND FAIR, PHILADELPHIA, in 1895 LADIES AND GENTLEMEN,—The—er this—er—welcome occasion gives me an—er—opportunity to make an—er—explanation that I have long desired to deliver myself of. I rise to the highest honors before a Philadelphia audience. In the course of my checkered career I have, on divers occasions, been charged—er—maliciously with a more or less serious offence. It is in reply to one of the more—er—important of these that I wish to speak. More than once I have been accused of writing obituary poetry in the Philadelphia Ledger. I wish right here to deny that dreadful assertion. I will admit that once, when a compositor in the Ledger establishment, I did set up some of that poetry, but for a worse offence than that no indictment can be found against me. I did not write that poetry—at least, not all of it. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Mark Twain (2004). Mark Twain's Speeches. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/3188/pg3188-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

OBITUARY POETRY

The $30,000 Bequest, and Other Stories by Mark Twain, is part of the HackerNoon Books Series. You can jump to any chapter in this book . POST-MORTEM POETRY (1) here POST-MORTEM POETRY (1) In Philadelphia they have a custom which it would be pleasant to see adopted throughout the land. It is that of appending to published death-notices a little verse or two of comforting poetry. Any one who is in the habit of reading the daily Philadelphia must frequently be touched by these plaintive tributes to extinguished worth. In Philadelphia, the departure of a child is a circumstance which is not more surely followed by a burial than by the accustomed solacing poesy in the . In that city death loses half its terror because the knowledge of its presence comes thus disguised in the sweet drapery of verse. For instance, in a late I find the following (I change the surname): Ledger Public Ledger Ledger DIED Hawks.—On the 17th inst., Clara, the daughter of Ephraim and Laura Hawks, aged 21 months and 2 days. That merry shout no more I hear,
          No laughing child I see,
     No little arms are around my neck,
          No feet upon my knee;

     No kisses drop upon my cheek,
          These lips are sealed to me.
     Dear Lord, how could I give Clara up
          To any but to Thee? A child thus mourned could not die wholly discontented. From the of the same date I make the following extract, merely changing the surname, as before: Ledger Becket.—On Sunday morning, 19th inst., John P., infant son of George and Julia Becket, aged 1 year, 6 months, and 15 days. That merry shout no more I hear,
          No laughing child I see,
     No little arms are round my neck,
          No feet upon my knee;

     No kisses drop upon my cheek;
          These lips are sealed to me.
     Dear Lord, how could I give Johnnie up
          To any but to Thee? The similarity of the emotions as produced in the mourners in these two instances is remarkably evidenced by the singular similarity of thought which they experienced, and the surprising coincidence of language used by them to give it expression. In the same journal, of the same date, I find the following (surname suppressed, as before): Wagner.—On the 10th inst., Ferguson G., the son of William L. and Martha Theresa Wagner, aged 4 weeks and 1 day. That merry shout no more I hear,
          No laughing child I see,
     No little arms are round my neck,
          No feet upon my knee;

     No kisses drop upon my cheek,
          These lips are sealed to me.
     Dear Lord, how could I give Ferguson up
          To any but to Thee? It is strange what power the reiteration of an essentially poetical thought has upon one's feelings. When we take up the and read the poetry about little Clara, we feel an unaccountable depression of the spirits. When we drift further down the column and read the poetry about little Johnnie, the depression and spirits acquires an added emphasis, and we experience tangible suffering. When we saunter along down the column further still and read the poetry about little Ferguson, the word torture but vaguely suggests the anguish that rends us. Ledger In the (same copy referred to above) I find the following (I alter surname, as usual): Ledger Welch.—On the 5th inst., Mary C. Welch, wife of William B. Welch, and daughter of Catharine and George W. Markland, in the 29th year of her age. A mother dear, a mother kind,
          Has gone and left us all behind.
     Cease to weep, for tears are vain,
          Mother dear is out of pain.

     Farewell, husband, children dear,
          Serve thy God with filial fear,
     And meet me in the land above,
          Where all is peace, and joy, and love. What could be sweeter than that? No collection of salient facts (without reduction to tabular form) could be more succinctly stated than is done in the first stanza by the surviving relatives, and no more concise and comprehensive program of farewells, post-mortuary general orders, etc., could be framed in any form than is done in verse by deceased in the last stanza. These things insensibly make us wiser and tenderer, and better. Another extract: Ball.—On the morning of the 15th inst., Mary E., daughter of John and Sarah F. Ball. 'Tis sweet to rest in lively hope
          That when my change shall come
     Angels will hover round my bed,
          To waft my spirit home. The following is apparently the customary form for heads of families: Burns.—On the 20th inst., Michael Burns, aged 40 years. Dearest father, thou hast left us,
          Here thy loss we deeply feel;
     But 'tis God that has bereft us,
          He can all our sorrows heal.

     Funeral at 2 o'clock sharp. There is something very simple and pleasant about the following, which, in Philadelphia, seems to be the usual form for consumptives of long standing. (It deplores four distinct cases in the single copy of the which lies on the Memoranda editorial table): Ledger Bromley.—On the 29th inst., of consumption, Philip Bromley, in the 50th year of his age. Affliction sore long time he bore,
          Physicians were in vain—
     Till God at last did hear him mourn,
          And eased him of his pain.

     That friend whom death from us has torn,
          We did not think so soon to part;
     An anxious care now sinks the thorn
          Still deeper in our bleeding heart. This beautiful creation loses nothing by repetition. On the contrary, the oftener one sees it in the , the more grand and awe-inspiring it seems. Ledger With one more extract I will close: Doble.—On the 4th inst., Samuel Pervil Worthington Doble, aged 4 days. Our little Sammy's gone,
          His tiny spirit's fled;
     Our little boy we loved so dear
          Lies sleeping with the dead.

     A tear within a father's eye,
          A mother's aching heart,
     Can only tell the agony
          How hard it is to part. Could anything be more plaintive than that, without requiring further concessions of grammar? Could anything be likely to do more toward reconciling deceased to circumstances, and making him willing to go? Perhaps not. The power of song can hardly be estimated. There is an element about some poetry which is able to make even physical suffering and death cheerful things to contemplate and consummations to be desired. This element is present in the mortuary poetry of Philadelphia, and in a noticeable degree of development. The custom I have been treating of is one that should be adopted in all the cities of the land. It is said that once a man of small consequence died, and the Rev. T. K. Beecher was asked to preach the funeral sermon—a man who abhors the lauding of people, either dead or alive, except in dignified and simple language, and then only for merits which they actually possessed or possess, not merits which they merely ought to have possessed. The friends of the deceased got up a stately funeral. They must have had misgivings that the corpse might not be praised strongly enough, for they prepared some manuscript headings and notes in which nothing was left unsaid on that subject that a fervid imagination and an unabridged dictionary could compile, and these they handed to the minister as he entered the pulpit. They were merely intended as suggestions, and so the friends were filled with consternation when the minister stood in the pulpit and proceeded to read off the curious odds and ends in ghastly detail and in a loud voice! And their consternation solidified to petrification when he paused at the end, contemplated the multitude reflectively, and then said, impressively: “The man would be a fool who tried to add anything to that. Let us pray!” And with the same strict adhesion to truth it can be said that the man would be a fool who tried to add anything to the following transcendent obituary poem. There is something so innocent, so guileless, so complacent, so unearthly serene and self-satisfied about this peerless “hog-wash,” that the man must be made of stone who can read it without a dulcet ecstasy creeping along his backbone and quivering in his marrow. There is no need to say that this poem is genuine and in earnest, for its proofs are written all over its face. An ingenious scribbler might imitate it after a fashion, but Shakespeare himself could not counterfeit it. It is noticeable that the country editor who published it did not know that it was a treasure and the most perfect thing of its kind that the storehouses and museums of literature could show. He did not dare to say no to the dread poet—for such a poet must have been something of an apparition—but he just shoveled it into his paper anywhere that came handy, and felt ashamed, and put that disgusted “Published by Request” over it, and hoped that his subscribers would overlook it or not feel an impulse to read it: (Published by Request) LINES Composed on the death of Samuel and Catharine Belknap's children by M. A. Glaze Friends and neighbors all draw near,
     And listen to what I have to say;
     And never leave your children dear
     When they are small, and go away.

     But always think of that sad fate,
     That happened in year of '63;
     Four children with a house did burn,
     Think of their awful agony.

     Their mother she had gone away,
     And left them there alone to stay;
     The house took fire and down did burn;
     Before their mother did return.

     Their piteous cry the neighbors heard,
     And then the cry of fire was given;
     But, ah! before they could them reach,
     Their little spirits had flown to heaven.

     Their father he to war had gone,
     And on the battle-field was slain;
     But little did he think when he went away,
     But what on earth they would meet again.

     The neighbors often told his wife
     Not to leave his children there,
     Unless she got some one to stay,
     And of the little ones take care.

     The oldest he was years not six,
     And the youngest only eleven months old,
     But often she had left them there alone,
     As, by the neighbors, I have been told.

     How can she bear to see the place.
     Where she so oft has left them there,
     Without a single one to look to them,
     Or of the little ones to take good care.

     Oh, can she look upon the spot,
     Whereunder their little burnt bones lay,
     But what she thinks she hears them say,
     ''Twas God had pity, and took us on high.'

     And there may she kneel down and pray,
     And ask God her to forgive;
     And she may lead a different life
     While she on earth remains to live.

     Her husband and her children too,
     God has took from pain and woe.
     May she reform and mend her ways,
     That she may also to them go.

     And when it is God's holy will,
     O, may she be prepared
     To meet her God and friends in peace,
     And leave this world of care. 1. Written in 1870. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Mark Twain (2004). The $30,000 Bequest, and Other Stories. Urbana, Illinois: Project Gutenberg. Retrieved October 2022 https://www.gutenberg.org/cache/epub/142/pg142-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at . www.gutenberg.org https://www.gutenberg.org/policy/license.html

POST-MORTEM POETRY (1)

Anne of Avonlea by L. M. Montgomery, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . Poetry and Prose Chapter XXIX - Poetry and Prose For the next month Anne lived in what, for Avonlea, might be called a whirl of excitement. The preparation of her own modest outfit for Redmond was of secondary importance. Miss Lavendar was getting ready to be married and the stone house was the scene of endless consultations and plannings and discussions, with Charlotta the Fourth hovering on the outskirts of things in agitated delight and wonder. Then the dressmaker came, and there was the rapture and wretchedness of choosing fashions and being fitted. Anne and Diana spent half their time at Echo Lodge and there were nights when Anne could not sleep for wondering whether she had done right in advising Miss Lavendar to select brown rather than navy blue for her traveling dress, and to have her gray silk made princess. Everybody concerned in Miss Lavendar’s story was very happy. Paul Irving rushed to Green Gables to talk the news over with Anne as soon as his father had told him. “I knew I could trust father to pick me out a nice little second mother,” he said proudly. “It’s a fine thing to have a father you can depend on, teacher. I just love Miss Lavendar. Grandma is pleased, too. She says she’s real glad father didn’t pick out an American for his second wife, because, although it turned out all right the first time, such a thing wouldn’t be likely to happen twice. Mrs. Lynde says she thoroughly approves of the match and thinks its likely Miss Lavendar will give up her queer notions and be like other people, now that she’s going to be married. But I hope she won’t give her queer notions up, teacher, because I like them. And I don’t want her to be like other people. There are too many other people around as it is. You know, teacher.” Charlotta the Fourth was another radiant person. “Oh, Miss Shirley, ma’am, it has all turned out so beautiful. When Mr. Irving and Miss Lavendar come back from their tower I’m to go up to Boston and live with them . . . and me only fifteen, and the other girls never went till they were sixteen. Ain’t Mr. Irving splendid? He just worships the ground she treads on and it makes me feel so queer sometimes to see the look in his eyes when he’s watching her. It beggars description, Miss Shirley, ma’am. I’m awful thankful they’re so fond of each other. It’s the best way, when all’s said and done, though some folks can get along without it. I’ve got an aunt who has been married three times and says she married the first time for love and the last two times for strictly business, and was happy with all three except at the times of the funerals. But I think she took a resk, Miss Shirley, ma’am.” “Oh, it’s all so romantic,” breathed Anne to Marilla that night. “If I hadn’t taken the wrong path that day we went to Mr. Kimball’s I’d never have known Miss Lavendar; and if I hadn’t met her I’d never have taken Paul there . . . and he’d never have written to his father about visiting Miss Lavendar just as Mr. Irving was starting for San Francisco. Mr. Irving says whenever he got that letter he made up his mind to send his partner to San Francisco and come here instead. He hadn’t heard anything of Miss Lavendar for fifteen years. Somebody had told him then that she was to be married and he thought she was and never asked anybody anything about her. And now everything has come right. And I had a hand in bringing it about. Perhaps, as Mrs. Lynde says, everything is foreordained and it was bound to happen anyway. But even so, it’s nice to think one was an instrument used by predestination. Yes indeed, it’s very romantic.” “I can’t see that it’s so terribly romantic at all,” said Marilla rather crisply. Marilla thought Anne was too worked up about it and had plenty to do with getting ready for college without “traipsing” to Echo Lodge two days out of three helping Miss Lavendar. “In the first place two young fools quarrel and turn sulky; then Steve Irving goes to the States and after a spell gets married up there and is perfectly happy from all accounts. Then his wife dies and after a decent interval he thinks he’ll come home and see if his first fancy’ll have him. Meanwhile, she’s been living single, probably because nobody nice enough came along to want her, and they meet and agree to be married after all. Now, where is the romance in all that?” “Oh, there isn’t any, when you put it that way,” gasped Anne, rather as if somebody had thrown cold water over her. “I suppose that’s how it looks in prose. But it’s very different if you look at it through poetry . . . and I think it’s nicer . . .” Anne recovered herself and her eyes shone and her cheeks flushed . . . “to look at it through poetry.” Marilla glanced at the radiant young face and refrained from further sarcastic comments. Perhaps some realization came to her that after all it was better to have, like Anne, “the vision and the faculty divine” . . . that gift which the world cannot bestow or take away, of looking at life through some transfiguring . . . or revealing? . . . medium, whereby everything seemed apparelled in celestial light, wearing a glory and a freshness not visible to those who, like herself and Charlotta the Fourth, looked at things only through prose. “When’s the wedding to be?” she asked after a pause. “The last Wednesday in August. They are to be married in the garden under the honeysuckle trellis . . . the very spot where Mr. Irving proposed to her twenty-five years ago. Marilla, that is romantic, even in prose. There’s to be nobody there except Mrs. Irving and Paul and Gilbert and Diana and I, and Miss Lavendar’s cousins. And they will leave on the six o’clock train for a trip to the Pacific coast. When they come back in the fall Paul and Charlotta the Fourth are to go up to Boston to live with them. But Echo Lodge is to be left just as it is. . . only of course they’ll sell the hens and cow, and board up the windows . . . and every summer they’re coming down to live in it. I’m so glad. It would have hurt me dreadfully next winter at Redmond to think of that dear stone house all stripped and deserted, with empty rooms . . . or far worse still, with other people living in it. But I can think of it now, just as I’ve always seen it, waiting happily for the summer to bring life and laughter back to it again.” There was more romance in the world than that which had fallen to the share of the middle-aged lovers of the stone house. Anne stumbled suddenly on it one evening when she went over to Orchard Slope by the wood cut and came out into the Barry garden. Diana Barry and Fred Wright were standing together under the big willow. Diana was leaning against the gray trunk, her lashes cast down on very crimson cheeks. One hand was held by Fred, who stood with his face bent toward her, stammering something in low earnest tones. There were no other people in the world except their two selves at that magic moment; so neither of them saw Anne, who, after one dazed glance of comprehension, turned and sped noiselessly back through the spruce wood, never stopping till she gained her own gable room, where she sat breathlessly down by her window and tried to collect her scattered wits. “Diana and Fred are in love with each other,” she gasped. “Oh, it does seem so . . . so . . . so hopelessly grown up.” Anne, of late, had not been without her suspicions that Diana was proving false to the melancholy Byronic hero of her early dreams. But as “things seen are mightier than things heard,” or suspected, the realization that it was actually so came to her with almost the shock of perfect surprise. This was succeeded by a queer, little lonely feeling . . . as if, somehow, Diana had gone forward into a new world, shutting a gate behind her, leaving Anne on the outside. “Things are changing so fast it almost frightens me,” Anne thought, a little sadly. “And I’m afraid that this can’t help making some difference between Diana and me. I’m sure I can’t tell her all my secrets after this . . . she might tell Fred. And what can she see in Fred? He’s very nice and jolly . . . but he’s just Fred Wright.” It is always a very puzzling question . . . what can somebody see in somebody else? But how fortunate after all that it is so, for if everybody saw alike . . . well, in that case, as the old Indian said, “Everybody would want my squaw.” It was plain that Diana did see something in Fred Wright, however Anne’s eyes might be holden. Diana came to Green Gables the next evening, a pensive, shy young lady, and told Anne the whole story in the dusky seclusion of the east gable. Both girls cried and kissed and laughed. “I’m so happy,” said Diana, “but it does seem ridiculous to think of me being engaged.” “What is it really like to be engaged?” asked Anne curiously. “Well, that all depends on who you’re engaged to,” answered Diana, with that maddening air of superior wisdom always assumed by those who are engaged over those who are not. “It’s perfectly lovely to be engaged to Fred . . . but I think it would be simply horrid to be engaged to anyone else.” “There’s not much comfort for the rest of us in that, seeing that there is only one Fred,” laughed Anne. “Oh, Anne, you don’t understand,” said Diana in vexation. “I didn’t mean that . . . it’s so hard to explain. Never mind, you’ll understand sometime, when your own turn comes.” “Bless you, dearest of Dianas, I understand now. What is an imagination for if not to enable you to peep at life through other people’s eyes?” “You must be my bridesmaid, you know, Anne. Promise me that . . . wherever you may be when I’m married.” “I’ll come from the ends of the earth if necessary,” promised Anne solemnly. “Of course, it won’t be for ever so long yet,” said Diana, blushing. “Three years at the very least . . . for I’m only eighteen and mother says no daughter of hers shall be married before she’s twenty-one. Besides, Fred’s father is going to buy the Abraham Fletcher farm for him and he says he’s got to have it two thirds paid for before he’ll give it to him in his own name. But three years isn’t any too much time to get ready for housekeeping, for I haven’t a speck of fancy work made yet. But I’m going to begin crocheting doilies tomorrow. Myra Gillis had thirty-seven doilies when she was married and I’m determined I shall have as many as she had.” “I suppose it would be perfectly impossible to keep house with only thirty-six doilies,” conceded Anne, with a solemn face but dancing eyes. Diana looked hurt. “I didn’t think you’d make fun of me, Anne,” she said reproachfully. “Dearest, I wasn’t making fun of you,” cried Anne repentantly. “I was only teasing you a bit. I think you’ll make the sweetest little housekeeper in the world. And I think it’s perfectly lovely of you to be planning already for your home o’dreams.” Anne had no sooner uttered the phrase, “home o’dreams,” than it captivated her fancy and she immediately began the erection of one of her own. It was, of course, tenanted by an ideal master, dark, proud, and melancholy; but oddly enough, Gilbert Blythe persisted in hanging about too, helping her arrange pictures, lay out gardens, and accomplish sundry other tasks which a proud and melancholy hero evidently considered beneath his dignity. Anne tried to banish Gilbert’s image from her castle in Spain but, somehow, he went on being there, so Anne, being in a hurry, gave up the attempt and pursued her aerial architecture with such success that her “home o’dreams” was built and furnished before Diana spoke again. “I suppose, Anne, you must think it’s funny I should like Fred so well when he’s so different from the kind of man I’ve always said I would marry . . . the tall, slender kind? But somehow I wouldn’t want Fred to be tall and slender . . . because, don’t you see, he wouldn’t be Fred then. Of course,” added Diana rather dolefully, “we will be a dreadfully pudgy couple. But after all that’s better than one of us being short and fat and the other tall and lean, like Morgan Sloane and his wife. Mrs. Lynde says it always makes her think of the long and short of it when she sees them together.” “Well,” said Anne to herself that night, as she brushed her hair before her gilt framed mirror, “I am glad Diana is so happy and satisfied. But when my turn comes . . . if it ever does . . . I do hope there’ll be something a little more thrilling about it. But then Diana thought so too, once. I’ve heard her say time and again she’d never get engaged any poky commonplace way . . . he’d have to do something splendid to win her. But she has changed. Perhaps I’ll change too. But I won’t . . . and I’m determined I won’t. Oh, I think these engagements are dreadfully unsettling things when they happen to your intimate friends.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. L. M. Montgomery (2022). Anne of Avonlea. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/47/pg47-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html. The lead image was generated using HackerNoon's Stable Disffusion Al Image Generator feature, via the prompt "Anne of Avonlea".

Poetry and Prose

Poor Folk by Fyodor Dostoyevsky, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . April 8th April 8th MY DEAREST BARBARA ALEXIEVNA,—To think that a day like this should have fallen to my miserable lot! Surely you are making fun of an old man?... However, it was my own fault—my own fault entirely. One ought not to grow old holding a lock of Cupid’s hair in one’s hand. Naturally one is misunderstood.... Yet man is sometimes a very strange being. By all the Saints, he will talk of doing things, yet leave them undone, and remain looking the kind of fool from whom may the Lord preserve us!... Nay, I am not angry, my beloved; I am only vexed to think that I should have written to you in such stupid, flowery phraseology. Today I went hopping and skipping to the office, for my heart was under your influence, and my soul was keeping holiday, as it were. Yes, everything seemed to be going well with me. Then I betook myself to my work. But with what result? I gazed around at the old familiar objects, at the old familiar grey and gloomy objects. They looked just the same as before. Yet WERE those the same inkstains, the same tables and chairs, that I had hitherto known? Yes, they WERE the same, exactly the same; so why should I have gone off riding on Pegasus’ back? Whence had that mood arisen? It had arisen from the fact that a certain sun had beamed upon me, and turned the sky to blue. But why so? Why is it, sometimes, that sweet odours seem to be blowing through a courtyard where nothing of the sort can be? They must be born of my foolish fancy, for a man may stray so far into sentiment as to forget his immediate surroundings, and to give way to the superfluity of fond ardour with which his heart is charged. On the other hand, as I walked home from the office at nightfall my feet seemed to lag, and my head to be aching. Also, a cold wind seemed to be blowing down my back (enraptured with the spring, I had gone out clad only in a thin overcoat). Yet you have misunderstood my sentiments, dearest. They are altogether different to what you suppose. It is a purely paternal feeling that I have for you. I stand towards you in the position of a relative who is bound to watch over your lonely orphanhood. This I say in all sincerity, and with a single purpose, as any kinsman might do. For, after all, I AM a distant kinsman of yours—the seventh drop of water in the pudding, as the proverb has it—yet still a kinsman, and at the present time your nearest relative and protector, seeing that where you had the right to look for help and protection, you found only treachery and insult. As for poetry, I may say that I consider it unbecoming for a man of my years to devote his faculties to the making of verses. Poetry is rubbish. Even boys at school ought to be whipped for writing it. Why do you write thus about “comfort” and “peace” and the rest? I am not a fastidious man, nor one who requires much. Never in my life have I been so comfortable as now. Why, then, should I complain in my old age? I have enough to eat, I am well dressed and booted. Also, I have my diversions. You see, I am not of noble blood. My father himself was not a gentleman; he and his family had to live even more plainly than I do. Nor am I a milksop. Nevertheless, to speak frankly, I do not like my present abode so much as I used to like my old one. Somehow the latter seemed more cosy, dearest. Of course, this room is a good one enough; in fact, in SOME respects it is the more cheerful and interesting of the two. I have nothing to say against it—no. Yet I miss the room that used to be so familiar to me. Old lodgers like myself soon grow as attached to our chattels as to a kinsman. My old room was such a snug little place! True, its walls resembled those of any other room—I am not speaking of that; the point is that the recollection of them seems to haunt my mind with sadness. Curious that recollections should be so mournful! Even what in that room used to vex me and inconvenience me now looms in a purified light, and figures in my imagination as a thing to be desired. We used to live there so quietly—I and an old landlady who is now dead. How my heart aches to remember her, for she was a good woman, and never overcharged for her rooms. Her whole time was spent in making patchwork quilts with knitting-needles that were an arshin [An ell.] long. Oftentimes we shared the same candle and board. Also she had a granddaughter, Masha—a girl who was then a mere baby, but must now be a girl of thirteen. This little piece of mischief, how she used to make us laugh the day long! We lived together, a happy family of three. Often of a long winter’s evening we would first have tea at the big round table, and then betake ourselves to our work; the while that, to amuse the child and to keep her out of mischief, the old lady would set herself to tell stories. What stories they were!—though stories less suitable for a child than for a grown-up, educated person. My word! Why, I myself have sat listening to them, as I smoked my pipe, until I have forgotten about work altogether. And then, as the story grew grimmer, the little child, our little bag of mischief, would grow thoughtful in proportion, and clasp her rosy cheeks in her tiny hands, and, hiding her face, press closer to the old landlady. Ah, how I loved to see her at those moments! As one gazed at her one would fail to notice how the candle was flickering, or how the storm was swishing the snow about the courtyard. Yes, that was a goodly life, my Barbara, and we lived it for nearly twenty years.... How my tongue does carry me away! Maybe the subject does not interest you, and I myself find it a not over-easy subject to recall—especially at the present time. Darkness is falling, and Theresa is busying herself with something or another. My head and my back are aching, and even my thoughts seem to be in pain, so strangely do they occur. Yes, my heart is sad today, Barbara.... What is it you have written to me?——“Why do you not come in PERSON to see me?” Dear one, what would people say? I should have but to cross the courtyard for people to begin noticing us, and asking themselves questions. Gossip and scandal would arise, and there would be read into the affair quite another meaning than the real one. No, little angel, it were better that I should see you tomorrow at Vespers. That will be the better plan, and less hurtful to us both. Nor must you chide me, beloved, because I have written you a letter like this (reading it through, I see it to be all odds and ends); for I am an old man now, dear Barbara, and an uneducated one. Little learning had I in my youth, and things refuse to fix themselves in my brain when I try to learn them anew. No, I am not skilled in letter-writing, Barbara, and, without being told so, or any one laughing at me for it, I know that, whenever I try to describe anything with more than ordinary distinctness, I fall into the mistake of talking sheer rubbish.... I saw you at your window today—yes, I saw you as you were drawing down the blind! Good-bye, goodbye, little Barbara, and may God keep you! Good-bye, my own Barbara Alexievna!—Your sincere friend, MAKAR DIEVUSHKIN. P.S.—Do not think that I could write to you in a satirical vein, for I am too old to show my teeth to no purpose, and people would laugh at me, and quote our Russian proverb: “Who diggeth a pit for another one, the same shall fall into it himself.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Fyodor Dostoyevsky (2000). Poor Folk. Urbana, Illinois: Project Gutenberg. Retrieved October https://www.gutenberg.org/cache/epub/2302/pg2302-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

Poetry is rubbish

Science and poetry are blended in a happy conjunction

The Essays of Adam Smith, by Adam Smith is part of HackerNoon’s Book Blog Post series. You can jump to any chapter in this book here . Of the Affinity between Music, Dancing, and Poetry. Of the Affinity between Music, Dancing, and Poetry. IN the second part of the preceding Essay I have mentioned the connection between the two arts of Music and Dancing, formed by the Rhythmus, as the ancients termed it, or, as we call it, the tune or measure that equally regulates both. It is not, however, every sort of step, gesture, or motion, of which the correspondence with the tune or measure of Music will constitute a Dance. It must be a step, gesture, or motion of a particular sort. In a good opera-actor, not only the modulations and pauses of his voice, but every motion and gesture, every variation, either in the air of his head or in the attitude of his body, correspond to the time and measure of Music. The best opera-actor, however, is not, according to the language of any country in Europe, understood to dance, yet in the performance of his part, he makes use of what is called the stage step; but even this step is not understood to be a dancing step. Though the eye of the most ordinary spectator readily distinguishes between what is called a dancing step and any other step, gesture, or motion, yet it may not perhaps be very easy to express what it is which constitutes this distinction. To ascertain exactly the precise limits at which the one species begins, and the other ends, or to give an accurate definition of this very frivolous matter, might perhaps require more thought and attention than the very small importance of the subject may seem to deserve. Were I, however, to attempt to do this, I should observe, that though in performing any ordinary action—in walking, for example—from the one end of the room to the other, a person may show both grace and agility, yet if he betrays the least intention of showing either, he is sure of offending more or less, and we never fail to accuse him of some degree of vanity and affectation. In the performance of any such ordinary action, every person wishes to appear to be solely occupied about the proper purpose of the action: if he means to show either grace or agility, he is careful to conceal that meaning, and he is very seldom successful in doing so: he offends, however, just in proportion as he betrays it, and he almost always betrays it. In Dancing, on the contrary, every person professes, and avows, as it were, the intention of displaying some degree either of grace or of agility, or of both. The display of one, or other, or both of these qualities, is in reality the proper purpose of the action; and there can never be any disagreeable vanity or affectation in following out the proper purpose of any action. When we say of any particular person, that he gives himself many affected airs and graces in Dancing, we mean either that he gives himself airs and graces which are unsuitable to the nature of the Dance, or that he executes awkwardly, perhaps exaggerates too much, (the most common fault in Dancing,) the airs and graces which are suitable to it. Every Dance is in reality a succession of airs and graces of some kind or other, and of airs and graces which, if I may say so, profess themselves to be such. The steps, gestures, and motions which, as it were, avow the intention of exhibiting a succession of such airs and graces, are the steps, the gestures, and the motions which are peculiar to Dancing, and when these are performed to the time and the measure of Music, they constitute what is properly called a Dance. But though every sort of step, gesture, or motion, even though performed to the time and measure of Music, will not alone make a Dance, yet almost any sort of sound, provided it is repeated with a distinct rhythmus, or according to a distinct time and measure, though without any variation as to gravity or acuteness, will make a sort of Music, no doubt indeed, an imperfect one. Drums, cymbals, and, so far as I have observed, all other instruments of percussion, have only one note; this note, however, when repeated with a certain rhythmus, or according to a certain time and measure, and sometimes, in order to mark more distinctly that time and measure, with some little variation as to loudness and lowness, though without any as to acuteness and gravity, does certainly make a sort of Music, which is frequently far from being disagreeable, and which even sometimes produces considerable effects. The simple note of such instruments, it is true, is generally a very clear, or what is called a melodious, sound. It does not however seem indispensably necessary that it should be so. The sound of the muffled drum, when it beats the dead march, is far from being either clear or melodious, and yet it certainly produces a species of Music which is sometimes affecting. Even in the performance of the most humble of all artists, of the man who drums upon the table with his fingers, we may sometimes distinguish the measure, and perhaps a little of the humour, of some favourite song; and we must allow that even he makes some sort of Music. Without a proper step and motion, the observation of tune alone will not make a Dance; time alone, without tune, will make some sort of Music. That exact observation of tune, or of the proper intervals of gravity and acuteness, which constitutes the great beauty of all perfect Music, constitutes likewise its great difficulty. The time, or measure of a song are simple matters, which even a coarse and unpractised ear is capable of distinguishing and comprehending: but to distinguish and comprehend all the variations of the tune, and to conceive with precision the exact proportion of every note, is what the finest and most cultivated ear is frequently no more than capable of performing. In the singing of the common people we may generally remark a distinct enough observation of time, but a very imperfect one of tune. To discover and to distinguish with precision the proper intervals of tune, must have been a work of long experience and much observation. In the theoretical treatises upon Music, what the authors have to say upon time is commonly discussed in a single chapter of no great length or difficulty. The theory of tune fills commonly all the rest of the volume, and has long ago become both an extensive and an abstruse science, which is often but imperfectly comprehended, even by intelligent artists. In the first rude efforts of uncivilized nations towards singing, the niceties of tune could be but little attended to: I have, upon this account, been frequently disposed to doubt of the great antiquity of those national songs, which it is pretended have been delivered down from age to age by a sort of oral tradition, without having been ever noted or distinctly recorded for many successive generations. The measure, the humour of the song, might perhaps have been delivered down in this manner, but it seems scarcely possible that the precise notes of the tune should have been so preserved. The method of singing some of what we reckon our old Scotch songs, has undergone great alterations within the compass of my memory, and it may have undergone still greater before. The distinction between the sounds or tones of singing and those of speaking seems to be of the same kind with that between the steps, gestures, and motions of Dancing, and those of any other ordinary action; though in speaking, a person may show a very agreeable tone of voice, yet if he seems to intend to show it, if he appears to listen to the sound of his own voice, and as it were to tune it into a pleasing modulation, he never fails to offend, as guilty of a most disagreeable affectation. In speaking, as in every other ordinary action, we expect and require that the speaker should attend only to the proper purpose of the action, the clear and distinct expression of what he has to say. In singing, on the contrary, every person professes the intention to please by the tone and cadence of his voice; and he not only appears to be guilty of no disagreeable affectation in doing so, but we expect and require that he should do so. To please by the choice and arrangement of agreeable sounds is the proper purpose of all Music, vocal as well as instrumental; and we always expect and require, that every person should attend to the proper purpose of whatever action he is performing. A person may appear to sing, as well as to dance, affectedly; he may endeavour to please by sounds and tones which are unsuitable to the nature of the song, or he may dwell too much on those which are suitable to it, or in some other way he may show an overweening conceit of his own abilities, beyond what seems to be warranted by his performance. The disagreeable affectation appears to consist always, not in attempting to please by a proper, but by some improper modulation of the voice. It was early discovered that the vibrations of chords or strings, which either in their lengths, or in their densities, or in their degrees of tension, bear a certain proportion to one another, produce sounds which correspond exactly, or, as the musicians say, are the unisons of those sounds or tones of the human voice which the ear approves of in singing. This discovery has enabled musicians to speak with distinctness and precision concerning the musical sounds or tones of the human voice; they can always precisely ascertain what are the particular sounds or tones which they mean, by ascertaining what are the proportions of the strings of which the vibrations produce the unisons of those sounds or tones. What are called the intervals; that is, the differences, in point of gravity and acuteness, between the sounds or tones of a singing voice, are much greater and more distinct than those of the speaking voice. Though the former, therefore, can be measured and appreciated by the proportions of chords or strings, the latter cannot. The nicest instruments cannot express the extreme minuteness of these intervals. The heptamerede of Mr. Sauveur could express an interval so small as the seventh part of what is called a comma, the smallest interval that is admitted in modern Music. Yet even this instrument, we are informed by Mr. Duclos, could not express the minuteness of the intervals in the pronunciation of the Chinese language; of all the languages in the world, that of which the pronunciation is said to approach the nearest to singing, or in which the intervals are said to be the greatest. As the sounds or tones of the singing voice, therefore, can be ascertained or appropriated, while those of the speaking voice cannot; the former are capable of being noted or recorded, while the latter are not. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Smith, Adam. 2018. The Essays of Adam Smith. Urbana, Illinois: Project Gutenberg. Retrieved May 2022 from https://www.gutenberg.org/files/58559/58559-h/58559-h.htm#G This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

The Essays of Adam Smith: Of the Affinity between Music, Dancing, and Poetry.

How to plan the unplannable One of my is outing her concern about our backlog to me. There is no way that we can do everything she wants to have with the budget that we have been given. It is my turn to tell her one of the wisdoms that I have learned in all these years of software development: Product Owners "Plan as if you will not get any more budget" Must, Should, Nice to Have We all know them, the castes of software features. Every Product Owner worth his salt would try to categorize the features of her product in these 3 buckets. And we all know that the is already a veiled It is like when you tell your kid that she will get that ice cream when we get home, knowing that she will fall asleep in the car. Nice to Have "won't do". The real problem is all the Especially once you have a first version of the software in the field. Suddenly bug and feature triage creep in. "This feature would be really cool, but if we do this other improvement we would get a bigger order from this other customer". And suddenly we leave the yellow brick road and get lost in the forest of improvements and bug fixes. "Should". And the output of the project team will get dragged down by unplanned issues introduced because of an operating system update, or an urgent security fix, or as banal as the end of life of an API that you rely on. So, what do you do in this case. My answer is: Measure your velocity, and plan as if your budget is all you have. Velocity One of the nicest features of Scrum SW development is that if you do feature refinement correctly and assign points to every task that the team works on, you will be able to measure the . velocity of the team Let me explain this using a car analogy. One of the most important sensors in your car is the one that shows how full your tank (or your battery, if you are driving an electric car), is. Most modern cars will have also an estimation of how far you can drive with the load you have. Scrum allows you to calculate a similar metric by means of velocity. Velocity is how many points can your team in average finalize every sprint. This can only be done if you are assigning points to your stories in the scrum Refinement meetings. Tools like Jira will calculate the velocity automatically for you. All that is left to do is to sum the points of your "should" stories and divide them by your team velocity. Knowing your budget would let you know how many sprints you can still afford, and you can plan accordingly. “Deciding what not to do is as important as deciding what to do.” (Steve Jobs) I know it is cheesy to quote Steve Jobs, but this is one of his wisdoms that has saved me more than once. Call to Action If you are a , calculate your velocity and use it to shape the list of "Should"s in your backlog. Make sure you do not plan your release until the very last sprint. You would not choose to drive to the gas station on the last drop when you drive. product owner If you are a , make sure you start calculating the velocity early and make your product owner and team members aware of its importance. scrum master If you are a , try to be accurate in your estimations. If you are too conservative you might remove some important features from the product. If you are too aggressive, you risk the project running out of gas before you ship the final version. software developer And quoting : . Good software is indeed like poetry. If you don't believe me look at all the games that live on despite not being supported anymore by their publishers. Many a poem would like to be so popular. Paul Valéry "A poem is never finished, only abandoned" First Published here

The Poetry in Software Releases

Create a new Poetry project: poetry new rocketship # poetry new <project-name> # Ex: This creates a Poetry project with the following directory structure: Activate the Python virtual environment: cd ./rocketship
poetry shell Deactivate the Python virtual environment: exit Install a Python package ( ): pip install poetry add requests # poetry add <package_name> # Ex: Uninstall a Python package ( ): pip uninstall poetry remove requests # poetry remove <package_name> # Ex: Installing dependencies: poetry install Display the package information: poetry show Lock the project dependencies: poetry lock Update the dependencies according to the file: pyproject.toml poetry update List the existing Python virtual environments associated with a Poetry project: cd rocketship
poetry env list Example: Delete the Python environment: poetry env remove rocketship-DKQKySEf-py3.8 # poetry env remove <python-environment-name> # Ex: Follow this space ( Vikas Z's blog ) for more on Python Poetry usage and hacks. Also published on Hashnode .

Quicknotes on Python Poetry

March 21st is , a day dedicated to one of the most treasured ways of expression around the world and linguistic diversity. I have always loved reading poetry with creative rhymes and melodic rhythm, and lately, I have come to appreciate free verse poetry as well. In any case, I would like to make time to read more poetry and discover new international poets. To achieve this goal, I created an n8n workflow that sends a poem translated into Romanian in my Telegram chat every day. In this article, I’ll show you how to set it up. World Poetry Day Workflow If this is your first n8n workflow, have a look at our first to learn how to install n8n. Once you have your n8n Editor UI open, there are two ways to follow this tutorial: either copy the workflow from into your Editor UI and deactivate the nodes, so that you can execute and test each node separately, or add the nodes one at a time. quick start guide here This workflow consists of four nodes: 1. : triggers the workflow every day at 10:00. You can change the time and interval based on your use case. Cron node 2. : makes an HTTP request to the that returns random poems. HTTP Request node Poemist API 3. : translates the returned poems into Romanian. You can choose from over 100 languages. LingvaNex node 4. : posts the translated poems in the chat. Telegram node Now let’s see how to set up each node. 1. Set the time First, you need to set the time and interval at which you want to receive poems in the chat. For this, set up the , where you can choose from seven modes and set the exact hour and minute For this example, the workflow will be triggered every day at 10:00. Cron node . 2. Get the poems Now, you need to get the poems. For this, set up the to get data from . Paste the and execute the node to test that it’s working. HTTP Request node Poemist Poemist URL 3. Translate the poems The Poemist API includes poems in different languages, which on one hand is great for linguistic diversity, but on the other hand, it can be challenging if you don’t know the language. To make sure you can read all poems, translate them into a language of your choice using the . For this, you need to sign up on to get credentials. You can find detailed instructions . Copy your credentials in , then set Romanian (or any other language you prefer). LingvaNex node LingvaNex here LingvaNex API Translate to In the field, select: Text The : title Current Node > Input data > JSON > 0 > title The : author Current Node > Input data > JSON > 0 > poet > name The : poem Current Node > Input data > JSON > 0 > content Now execute the node to test that it’s working. 4. Send poems to Telegram Finally, you need to send the requested poems to your Telegram chat. In your Telegram account, start a chat with and follow the instructions to create a bot and get credentials. Then, go to the Telegram node and add the credentials to . Botfather Telegram API Next, you need to fill in the of the newly created bot. There are two ways to get your Telegram Chat ID: with the or with a Telegram bot. You can find instructions for both methods . Chat ID Telegram Trigger node here After completing the , you need to set up the text you want to send to the chat. Open the field and select the poem translation from . You can add more text or emojis to prettify the message. Chat ID Text Current node > Input Data > JSON > result Now execute the whole workflow and check your Telegram for an incoming message: Finally, save and activate the workflow, so that it runs every day at the scheduled time. Next steps That was it! Now you know how to get international poems, translate them,  and send them to a Telegram chat to get your daily dose of poetry. If you run into issues while following this tutorial, you can message me on or ask for help in our . Twitter community forum

Using an API to Return a Daily Poem in Telegram to Celebrate World Poetry Day

I have become a ‘covidiot’ nowadays. I’m stuck in the home since last one and half months since COVID-19 outbreak. There is hardly any physical activity and I’m spending the longest era of my life without underwear since my adulthood. Life is moving like a tortoise and my brain has started to malfunction sometimes. The propensity of blogging has increased a bit nowadays. I’m pretty average in writing nonfiction. Sometimes I write hunky-dory semi-flat fictions Once in a blue moon, I write some pathetic verses but those grow bigger than ‘Thanos’ and devastate me in my dreams. Once upon a time, I got 51 thumbs down in a poetry platform for publishing violent poetry. Yes, 51! I remember the cold figure. but I am a terrible poet! Look, I realized long ago that I couldn’t become a poet. I don’t try that anymore. I’m going to try something else. Artificial intelligence is being used widely nowadays. AI is getting new use cases every day. A few days ago, I came across a new about Deep-speare AI. The AI model is basically a joint neural model of poetic language, meter and rhyme. Deep-speare can write verses like Shakespeare and most readers are unable to differentiate from the original human-written poems. Remarkable achievement in the AI field. research paper Deep-speare isn’t available for public usage right now (at least I didn’t find it). But I found some other AI alternatives to feed a dose of enjoyment to my idle mind. An AI Experiment With POEMPORTRAITS is an online experimental site which generates a poetic line from a single word input of the user. They ask you to donate a word of your choice and take a self-portrait. The process is smooth. POEMPORTRAITS Their AI algorithm expands the donated word into original lines of verse. The algorithm is trained on millions of words of 19th-century poetry. Sounds interesting? I just tried it. Convergence (I tried to be tricky with them) My donated word: They provided me with a unique POEMPORTRAIT of my face. The lines of the AI poetry illuminates my face here. Looks cool. Good fun! The AI model is ever-evolving and making itself perfect day by day. The output: An AI Experiment With Poem-generator is a site which uses AI to craft a full poetry. Yes, you hear it right. A poem fully generated by AI. You need to provide some words as inputs and you need to select the mood of the poem. I wanted to give them a tough task. Poem-generator So, I wanted to create a sonnet. Sonnet’s 14-line length and its two-part ‘argument’ structure can be tough for the AI bot. I selected ‘love’ mode. Here is my input: And this is the output: Ode to the Girl -A Sonnet by paragism My caring girl, you inspire me to write. How I love the way you gaze, walk and sleep, Invading my mind day and through the night, Always dreaming about the darling gaze. Let me compare you to a long ember? You are more blazing, glorious and round Stark frost nips the robins of December. And wintertime has the darling compound. How do I love you? Let me count the ways. I love your amazing cheek, hair and eyes. Thinking of your daring hair fills my days. My love for you is the aesthetic fries. Now I must away with a staring heart, Remember my round words whilst we're apart. A sonnet generally throws a question and gives an answer. The poem captures the flow very well. Some words look insensible but I can discount those. Some parts are heavily inspired from some popular poems but a layman will hardly understand. I didn’t try this but it was possible for me to alter a few words to make it more meaningful. Overall, I’ll rate the AI job as very decent. Not bad. What do you say? Heard about the programmer poet of 1960s? South African-born won Nobel prize in literature in 2003. He started his career as a programmer with IBM surprisingly and then, in the 1960s, worked with the Atlas 2 supercomputer at the United Kingdom’s Atomic Energy Research Establishment. J.M. Coetzee Coetzee published a fictionalized autobiographical memoir titled ‘Youth’ in 2002. The protagonist’s name was John. Coetzee wrote in that book: “Although Atlas is not a machine built to handle textual materials, he uses the dead hours of the night to get it to print out thousands of lines in the style of Pablo Neruda, using as a lexicon a list of the most powerful words in The Heights of Macchu Picchu.” In his real life, Coetzee wrote specific codes to generate verses on the British supercomputer and that was 1960s! He also published some of them after alterations. Coetzee’s experiments didn’t find much attention that time as programmers weren’t interested in verses and poets weren’t interested in programming. Coetzee was the first programmer poet in the history. But Coetzee created the impossible bridge between programming and poetry. Today’s AI poetry or literary work is only an extension of that. History of technology is really strange. AI poetry is definitely experimental but don’t miss the fun quotient. Can a combination of AI and human intelligence create the next generation of poems? What’s the harm? Coetzee tried it almost 60 years back!

My Experiments With AI Poetry And Some Random Thoughts

A while ago I’ve continued to use Spell, and have expanded into exploring other training models. In this post I’m going to show you how to make a poetry bot. I published a post about how I used Spell, a machine learning framework that allows you to train your models faster without the pain of dependency management on your machine, to implement a style transfer. Today I wanted to write about making your own text bot with Spell. I’ve always been a huge fan of Emily Dickinson’s poetry. I know some find her work a bit morbid, but her poetry has spoken to me throughout many years and I continue to marvel at how someone who rarely left her home could have such incredible insight into the human condition, the natural world, and the realities of life and death. A portrait of Emily Dickinson, the famous reclusive poet Since Spell conveniently had a video tutorial for creating a bot trained on lyrics from DOOM, I figured I could apply this quite easily to Emily Dickinson’s poetry. Surprisingly for me, the hardest part was not the training but the web scraping component. I started out with the and then poked around some documentation for puppeteer. I also looked at cheerio to figure out how I could get the scraper to press the “next” button. This was necessary for when it reached the end of the results on a page. Node.js tutorial for web scraping At first I decided to scrape poets.org, which only had 5 pages of poetry by Emily Dickinson. It seemed like a paltry amount, and I knew Emily Dickinson had been very prolific. So, I did some searching online to find a better source. Although a bit more difficult to scrape, poemhunter.com ended up being a better source. It had 31 pages of poetry by Emily Dickinson. Jackpot! I used NodeJS for scraping a website with all of Emily Dickinson’s poems I did run into some issues at this point, with lots of errors about the socket hanging up that I thought was crashing the scraper. It was hard to deduce exactly what was the cause, but by modifying my file writing function to add each poem to the file one by one instead of appending each poem to an increasingly long string and writing the file at the end, I still got the data back that I was expecting. All of Emily Dickinson’s poems were added to the same text file. This made it easier for the LSTM training model to process the data. Once the model was created, I downloaded it back to my machine and created a small web app with ML5. The app uses the model to generate new poetry, with an adjustable variable called “temperature”. The variable allows you to change the amount of randomness you see in the generated text. As opposed to the AI drawing purely from the poetry data in the file. Here is a brief sample of output from the bot, for your reading pleasure: Birds at the Corn— The Sun— With Men Orchard with Me— The Bone at House— The Bonnet Day— The Milly strain of He can the March— And then I star me— And Death— A Dread His Eyes the Sun— And then the Sun too Day the Birds— The Room To only still— And I too see the Soul That Desert face of Sun— The Man As House He stand— And stand to the Soul a Bee— And then the Soul as Beauty If you’re interested in creating your own text bot with Spell, check out this which I used: video tutorial Hopefully now you have a good idea of how to make a poetry bot! Of course if you’re having any trouble and want to see my code, . I have it up on github here

How To Make a Poetry Bot Using Spell

Why I Still Love Writing HTML, CSS, and JavaScript Believe it or not, I’ve made a career for the past decade out of writing pure HTML, CSS, and JavaScript. While I do as a software engineer, coding mostly with PHP and JavaScript, I am still learning how to write code in NodeJS and ReactJS, because that is technically what most tech companies are looking for nowadays. Most companies won’t even acknowledge you if you have no experience with JavaScript, but my actual living for the past decade has come from web design, specifically in writing pure HTML, CSS, and JavaScript — and for the past few months, I’ve also found great work as a technical writer for . run my own business RunCloud A recent article made me realize just how much the world of web design is starting to experience : those who know JavaScript design and those who don’t. In short: The Great Divide on one side, an army of developers whose interests, responsibilities, and skill sets are heavily revolved around JavaScript . On the other side, an army of developers whose interests, responsibilities, and skill sets are focused on other areas of the front end, like HTML, CSS , design, interaction, patterns, accessibility, etc. Photo from CSS Tricks: The Great Divide We rarely acknowledge or recognize it, but the latter is being phased out quickly and hushedly, while the former remains highly in demand. The shift in what companies are looking for requires the latter educate themselves in order to remain relevant in modern technology. The salary demands of the former are also much higher than the latter. There are hundreds to thousands of jobs that need to be filled every year, but often go unfulfilled. Unfortunately, it is the way of the world, and I strongly recommend the latter hop on board and start learning JavaScript fast. When programming or designing, I reflect back on the days when I thought HTML, or HyperText Markup Language was the best thing that happened to the world. It was a language that I knew that the world barely knew. To the rest of the world, the magic just happened. To me, this HTML code made the magic happen. I didn’t know HTML and the way I learned it was by simply clicking on View Source. What I saw the frontend and what it revealed to me on the backend was vastly different, yet magical. We often take for granted such code. Most people today have no idea that CSS and JavaScript did not always exist and we all relied on HTML for our “visual” needs. Many years ago, we couldn’t do half of the things we do so easily today. In 1995, , and you could mostly do simple commands like alert and write. More importantly, you could write more complex commands like mathematics and accept user input. Netscape Navigator paved the way for such a language to progress and expand. Internet Explorer, Opera, and later on, Firefox and Chrome would use and accept JavaScript as if it was a given. VBScript also had its reign for quite some time, but the advancement of JavaScript has allowed it to thrive into new decades, expanding upon its usefulness and functionality. JavaScript came to fruition Before 1995, , creating individual HTML pages that looked similar, or might be different, all hand coded into the templates themselves. This could easily number into the hundreds to thousands of individual page creation, which would eventually give rise to DHTML, or , and then ultimately, to the CMS, or , where pages could be loaded through database calls and eventually, a , for fastest loading speed times. every page needed to be designed and many designers would have to copy the same template over and over Dynamic HTML Content Management Systems caching system The result being that instead of creating hundreds to thousands of pages individually, you could load a single page every time and a call to a database for that web page would load up the content, eliminating the physical need of page creation. Once CSS, or , came to full adoption by the entire web community, it made things much easier, as pages could look the same in a single line of code. The beauty of CSS was that you could place CSS inline to change templates while still having the general template look like every other page. Cascading Style Sheets , as mentioned above, creates a barrier for the fact that most companies are now looking for the former: JavaScript soldiers while completely writing off the knowledge of the HTML/CSS workers. The reason likely being is that backend and frontend programming can easily be mixed with the available npm libraries, making the syncing process of frontend developers and backend developers easier. Therefore, the former are more likely to get hired rather than the latter, and the latter must now work to update their knowledgebase to include JavaScript. If they do not, they are likely to become obsolete and there is nothing they can actually do about it. Luckily for the companies I have worked for, they had only required me to know the latter, but in applying to newer companies, I realize that I now have to meet their required standards. The Great Divide ReactJS and NodeJS and all things that require more complex JavaScript beyond just adding a script to the page are far different than just looking at “View Source” and figuring out how things work. Instead, it requires full , understanding , and learning the . You can also add in to the knowledgebase. Learn all of these — and you will find yourself having a job for the next 20 years until they come up with something new and different and hip with “modern company standards”. knowledge of working JavaScript how to setup and use ReactJS complete work of NodeJS Vue.js In fact, with no relation at all, but my total respect to him, you should probably just follow and read everything he writes, as he seems to know everything there is to know about JavaScript. There is no doubt that although website says it takes 91 minutes to read his complete JavaScript Handbook, it probably took Flavio months to actually write it, and sharing it with the community for free at large — makes him one of the most generous people in the world, when it comes to teaching and kindness. Flavio Copes Medium FreeCodeCamp’s As I continue to write code and choose my designs and libraries, I still can’t help but take a look at the code that makes everything I do possible. Oftentimes, I’m fixing bugs, but there comes a point where most of the bugs are gone and I just get to admire my work. The evolution and beauty of the code, made possible by the web browser, to magically render all things we see on the frontend and process them on the backend. With a combination of JavaScript, HTML, and CSS — and focus on frontend development, we often forget the poetry of code that streamlines and makes our world possible.

Admiring The Poetry Of Code

This is a follow up to my article on generating Walt Whitman stye poetry using Deep Learning: https://hackernoon.com/i-tried-my-hand-at-deep-learning-and-made-some-poetry-along-the-way-2e350c33376f As I have been on an app-building role, I figured why not convert the model into an app as well. Once you have a trained Deep learning model, it can be a straightforward step to setup an app using it. My initial inspiration for doing this project was to participate in the NaNoGenMo series: https://github.com/NaNoGenMo/2018 This is an annual competition that runs in November where people try to train algorithms to write novels. Unfortunately, we haven’t yet cracked the puzzle to write something worth reading that long using an algorithm (every year we get closer though!). I settled on generating poetry because it’s easier to sound convincing (yay for art). And the poetry was…interesting. You can see it by using the app: https://leaves-of-ai.now.sh/ You can give it a root word or phrase and it will generate a verse starting from that. Pretty neat. But it doesn’t end just here. Because now everything is setup, you can easily change the dataset and get a whole new app. Say you want to get some Shakespeare generated text. All you would have to do is change the dataset to that of Shakespeare’s plays and you have an AI Romeo and Juliet app. :) One of the fastai students actually took my app and put his own spin on it and made an Elon Musk tweet generator! Hilarious and probably a way better idea than mine. Have any cool ideas for this kind of an app? Let me know in the comments. This project was built using the fastai library (which is in turn built on Pytorch). I used an AWD-LSTM based char-RNN network to generate our text. You can find the full code here: https://github.com/btahir/leaves-of-ai

Building A Walt Whitman Poetry Generator App

In I looked at various to help address some of the difficulties you may encounter when rebasing a set of changes. Crucially what I didn’t talk about was why you might want to rebase a set of changes in the first place or what a great end result might look like. How to rebase safely for profit and pleasure techniques First of all, the why Developers often talk about “being in the zone”. Certainly it’s the case that some complicated problems require you to get into the right mindset and build a good mental model of the problem in order to be able to solve them effectively. This mindset is very different from the mindset that is needed to write good commit messages which for reasons we will discuss later should be focused on the narrative and less on the technical. At the same time waiting until we have finished a job in its entirety so that we can take our code-wrangling hat off and put on our commit message writing hat is also problematic. We can end up in the undesirable situation where we have a working tree littered with updated, created and deleted files and it’s hard to pick apart the steps we’ve taken to get to the end result. Sometimes it is not even possible because a file has gone through several iterations of changes to get to the end result. We end up with a single massive commit, perhaps encompassing several smaller tasks, because it is too difficult to pick everything apart now that we have done it. This sucks for anyone who has to review your code and it sucks for you in 2 years time when you come across the commit in a blame and have to decipher the mess again to understand why you made the changes you did. git Can you quickly review my code for me?… Photo by on Simson Petrol Unsplash The solution to both of these problems is to commit small, commit fast and commit often. This means that you always have a small number of changes in each commit. If you are TDDing a good place to start is each new test and its associated code change in each commit. Committing fast means that we don’t waste time and risk losing momentum by worrying about the finer details of the commit message. We get just enough information in that we can identify the commit later and perhaps a little memory jog if there are some important specifics we think we might forget. In practice this means usually using the syntax for adding commits. This forces you to be brief. I usually prefix commits that I add in this way with a particular character ( is my usual choice) so that I can identify them later. Committing often is a natural consequence of committing small. It should become part of your normal red-green TDD cycle. git commit -m "..." — Then once the problem is solved and you know the steps that were required to reach the solution, you are in a much better position to reorganise these into a coherent set of commits. In this sense it is like refactoring or performance optimisation. If you try and do it at the start, it is more likely that you refactor the wrong thing or add complexity optimising code that turns out not to be a bottleneck. It is only once the job is done you can identify the best way to improve it. Similarly with preparing a set of commits — it is only once you know all the changes that are required that you can identify the best way to structure them into coherent commits. There are other reasons you may want to rebase your commits prior to merging them. Lots of things can happen whilst you are working on a job, not least the job itself may change. Perhaps this kind of thing may look familiar… There’s a bunch of different jobs going on here and a lot of redundant information. It benefits no-one to keep all this in the commit log of the application. All that really needs to be kept is It is important that your commit log contains the correct granularity of information. You want to maintain separate commits for separate tasks. At the same time, unnecessary commits will just get in the way when you are trying to track down the source of a problem. Ultimately rebasing commits and rewriting changes is about efficiency. The aim is to trim away any cruft and distractions whilst ensuring that all the information needed to understand the set of changes is clearly and easily available. Now the what So what do good commit messages and pull requests look like? The first thing to recognise is that, like code, commit messages are written once and read many times. So in order to identify what makes a good commit message you need to consider who the audiences are that you are writing for. There are 3 key audiences that you need to think about. You The first person is yourself. One of the most useful parts of the rebasing and commit writing process is sorting the changes you have made into the different steps and tasks that you took. Here is where you take your code from good to great. Do you understand why each individual change within a commit was necessary? What does it achieve? Do your changes follow a logical progression? Now that it works could you do the same thing in a better way? Have you done everything that is required for the story? Have you missed any edge cases? Did you skip a test here or there? etc etc etc You should be able to split your work into clear coherent chunks and then it should be easy to describe what you were trying to achieve and why you chose the solution you did. If your commit includes lines that start with things like ‘Also changed…’ that’s a smell that you have bundled more than one change into the same commit Your team The next set of people you are writing for are your team. Assuming all your code goes up for code review — and it should — the easier you can make it for your team to understand your proposed changes the better it is for everyone. Coherent focused commits with an explanatory message mean that people can quickly and effectively review your code without getting bogged down in trying to figure out what is going on or why a particular change was required. It means you will get better feedback and your team mates will be more willing to review your changes because they will feel more like it will be a constructive and efficient use of their time. Your commit messages should always focus on the narrative of the changes and not the the technical details. Anyone reviewing the code will be able to see the technical changes from the diff. If you are writing things like ‘Changed class X in file Y to call method Z` you are wasting everyone’s time as the diff says exactly that in a more precise and efficient manner. What is interesting is why did you do that particular change. Is there any context that may result in you choosing this solution over something that on the surface may be more obvious? Your commits should guide the readers of your PR through the changes that you have made. If it is a complex set of changes they should be broken into separate steps so that it is easy to follow, even if it means that the same code gets modified in multiple commits throughout the PR. Reading through the set of commit messages on a PR should be sufficient to explain the “what” and the “why” of the changes. The final “how” should be explained by reading the code itself. You again in 2 years or 5 years or 10 years The final audience you are writing for is your future self. Imagine you are neck deep in git archeology trying to figure out how some code arrived in a particular state and this commit comes up. What would you want to know in order to understand why this set of changes was made in the way that it was? Bear in mind that much of the context you may think is obvious now probably won’t be obvious then. The project that is consuming your life at the moment will be nothing but a distant memory, the painful 3 hour meeting you’ve just sat through hammering out different possibilities with the stakeholders will be long forgotten and all you will have to explain this set of changes is the paragraph or so at the top of the commit. At this point, which of these would you rather see? A completely useless commit message A commit message that might actually be of some use to some one In order to write effectively for all of these different audiences you need to be able to take your time and focus on this as a separate task to writing the code itself. It is a very different skill and one that should be practised mindfully as it is as important a skill for developers as writing the code. At least bad code can be fixed later. This is why trying to do this whilst maintaining a code-writing mindset is futile and inefficient. As a final note here are a couple of other things to consider when writing commit messages and pull request messages. Commits are part of the repository, pull requests aren’t If you want to reference previous changes it can be tempting to link to a pull request. However pull requests are not a feature of git, they are specific to the particular git hosting provider you are using at the time. If you change provider, all those links to PRs now become useless. It may be that one day a new super awesome git hosting provider appears on the scene that you would like to try. It is much better not to have to consider that losing all your pull request information is a big drawback or that your commit log will now contain lots of broken links. There are two implications of this. The first is that you should link to commits rather than pull requests in commit messages. Reference them by SHA and let Github, Bitbucket or whatever tool you are using convert them to links. Then they will always work regardless of the tool you are using. The second is that all important information should be in the commit messages, not the PR message. Depending on how your provider handles merges, you may still end up with the PR message in the merge commit but it is still much better to have the important details with the relevant commits, even if this means repeating some information from commit to commit. This means that if the commit does show up in several years time as part of a git blame, the chances of the person seeing the information is greatly increased. A pull request should tell a story A pull request should have a clear goal that can be written as a narrative. In many ways it echoes the guidelines to writing a good agile story. It should have clear motivations and beneficiaries. It should be written from a business perspective and be as non-technical as possible. It’s a bit like the summary that appears on the back of a book. Then the commits are chapters within that story and the commit messages should read as such. Each one is a step towards achieving the overall goal laid out in the pull request. Finally the diffs provide the individual code changes that were required for each chapter. Just as it is redundant to repeat all the information contained in the diff in the commit message, it is redundant to repeat the information in the commit messages in the pull request message. The pull request message should be aimed at code reviewers since this is its primary audience (quite possibly its only audience). It should be brief and non-technical. Don’t invest a lot of time in the pull request message as it is the most transient of all, save your energy for the commit message. The exception here is when the pull request consists of a single commit. In that case the PR message should simply be the commit message, which most providers will do by default anyway. So having looked at some of the motivations for using git rebase to prepare our pull requests and some examples of what to do, the next question is how to put that into action. For help with that, check out . How to rebase safely for profit and pleasure

The poetry of pull requests

Correlation is not causality Moderation is not morality Certification is not ability Mobilization is not mobility Educated is not all-knowing Constipated is not at all flowing Darting is not bowling R.R. Martin is not J.K. Rowling A free lunch cannot be supersized The revolution will not be centralized Grown ups might not be adults All nations might not be cults Lawyers are not under oaths The emperor has no clothes Counterfeiting is not a crime is more sublime Quantitative easing Caracas is not Mogadishu Block size is not the issue A free lunch cannot be overpriced The revolution will not be centralized Your opinion is not science Being a minion is not defiance Having anti-virus is not being immune The Pirate Party can’t win too soon On the news is not a fact You can choose to not react Stevie Wonder is not Steve Wozniak Choose the shortcut and not the cul de sac A free lunch might make you realize The revolution will not be centralized

A Bit of poetry

It was a dark, grey winters evening and I found myself, as I had done way too many times in the past, staring at my computer screen endlessly scrolling through useless articles ranging from snowflaky self-help to brain melting tutorials. Phew, that was a long sentence. Anyways, for reasons I can’t remember I found myself reading this article: https://www.digitaltrends.com/cool-tech/japanese-ai-writes-novel-passes-first-round-nationanl-literary-prize/ An AI wrote a novel, and whats more, it almost won a literary prize! So, not only was it not garbage, it was good enough to fool the experts! I was intrigued, and started googling away… I found out that there actually is a where people submit their best attempt at generating a novel that is at least 50,000 words. I looked at some of the code/outputs and was really intrigued. You can find it here: National Novel Generation Month https://github.com/NaNoGenMo And then as if I wasn’t frothing in the mouth from excitement already, I read this: https://github.com/zackthoutt/got-book-6 A guy wrote the next game of thrones book using deep learning! All sorts of thoughts raced through my head. I could see it now… I was going to take some data and put it through my amazing algorithm. I was going to publish a novel. It was going to become a best seller. The next big fantasy series. I’d be doing pretty well with book sales. Netflix would then come and secure rights to my book. They would make a trilogy of movies. I’d get to meet Jennifer Lawrence. I’d be doing really well now. They would invite me for an interview on TV. The interviewer would gush at my work and tell me how she’s such a big fan and ask me what’s the secret to my, seemingly, superhuman ability to produce so many amazing novels. I’d give her a smug grin, look at the camera, and shout: “Haha, you idiots! I just fed all the Wheel of Time books through an algorithm I stole from github from some random dude! You’re like the people in that Al Pacino movie where he makes that Simone software. You got Simoned!” Pandemonium would break out. People would start questioning their reality. They would be afraid to pick up another book in case their favorite author turns out to be a machine. I couldn’t wait. I set about executing my devious plan. 30 minutes later… I gave up. Yeah, turns out most algorithms are not that great at churning out good novels. In fact, they produce really incoherent, and kind of funny, outputs: “i had inherited the company because of the future putting his brother in applause. parents was a stupid success, madam, now indeed, and female form in individual color. now the rant happened and closet, maiden, always won for any present, in six.” I clearly wasn’t going to be impressing anyone, let alone Netflix and Jennifer Lawrence, with that prose. I was disappointed. I had no experience in deep learning and no resources to consume a ridiculous amount of data, so I could scarcely hope to beat these efforts made by so called experts. If only there was genre where these random words could be interpreted as genius. And then it hit me. Poetry! What is poetry but a bunch of random words thrown together? It’s the equivalent of modern art in literature. Okay, I apologize to anyone who loves and reads poetry. I am sure it can be beautiful and meaningful. But it’s never really appealed to my unsophisticated tastes. I tend to prefer a plain worded fairy tale with swords. And dragons. And wise old men with long white beards. But I was curious to try it out and see what kind of output I could get with poetry. So began my little project. Data The Data I decided to use was Walt Whitman’s Leaves of Grass. Even a plebeian like me can appreciate Walt Whitman! You can find this at Project Gutenberg which is a resource for non-copyright works or those that are now in the public domain: https://www.gutenberg.org/ I found the text file for Leaves of Grass and saved it down on my computer. Let’s call it data.txt. Algorithm I decided to use Zach Thoutt’s algorithm which he had used to generate the next book of Game of Thrones: https://github.com/zackthoutt/got-book-6 Where do I run this? One thing you need to know about deep learning is that you need of computing power to run the models. Ideally, you need a GPU resource to do the heavy lifting for you. I did not have a GPU in my possession but luckily I had dabbled (emphasis on the dabble) with deep learning before and signed up for Jeremy Howard’s course on it: a lot http://www.fast.ai/ In the fast.ai course you run all your models on the cloud so you are not constrained by your machine. We setup an EC2 instance on Amazon Web Services (AWS) which has the GPU power behind it (this would be the P2 instance). You need to request Amazon to give you access to this; which you can if you are a member of his course. Once you have your instance running, you then run your code in a Jupyter notebook hooked up to that instance. I felt that setting up all this to run your deep learning model was a pain for a layman like me so I am going to do a step-by-step walkthrough on how to do this. Now, there are many ways to do this. But I am just going to show you the way I did it. It might not be the best way. But it works. Finally, the tutorial I am assuming you know how to start EC2 instances. For this, you want to use one of the AWS Deep Learning AMI. This way you do not have to worry about installing any of the deep learning packages. I selected the AWS Deep Learning AMI (Amazon Linux). Now, select a p2 instance. This would probably be the p2.xlarge instance unless you’re a big shot who got approved for an even bigger instance. Once you are okay with everything, launch your instance. Now, open up a terminal and connect to your EC2. You know the drill: use the terminal in Mac or Putty in windows. You can find out how to SSH into your instance by right clicking on your EC2 instance and choosing the Connect option. The command will be similar to this: ssh -i your-ec2-key.pem ec2-user@ec22–212–21–23–21.compute-1.amazonaws.com You’re in! And everything is already setup because we selected the Deep Leaning AMI. Well, everything except for a few tiny things… One of the libraries used for deep learning is Tensorflow. We want to use Tensorflow version 1.0.0 for this exercise. The reason is that the github code we will be using breaks on later versions. It’s probably a simple enough update to change the code to fix this but I am lazy and just want to run this ****. We need to change our version by first uninstalling the existing Tensorflow package and re-installing 1.0.0. #Uninstallpip uninstall tensorflow # Install version 1.0.0pip install tensorflow==1.0.0 Then we need to optimize our GPU settings because Amazon for some reason does not do this automatically: # optimize GPUsudo nvidia-persistencedsudo nvidia-smi — auto-boost-default=0sudo nvidia-smi -ac 2505,875 Another thing we need to do to insure that our deep learning algorithm actually uses the GPU on this instance is to set the library path for CUDA: export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64 Done! Now we are ready to start up Jupyter. You need to run this command: jupyter notebook --no-browser --port=8888 Obviously, this is not straightforward as well. You need to now open up a new tab/window in your terminal. And run this command (with your key and EC2 ID) so you can run Jupyter on local host 8000: ssh -i EC2key.pem -L 8000:localhost:8888 ec2-user@ec2-21-21-21-21.compute-1.amazonaws.com Okay! Now we are really ready to start coding aka copy pasting someone else's code. Open up localhost:8000 and you should see Jupyter starting up. You might need to authenticate to access it in which case you need to pass in a string in the URL. This can be found in the output in your terminal where you ran the Jupyter notebook command. Now, we need to move the data inside our notebook. I am assuming you’ve been a great follower and have already saved down the data. We called it . You can easily move this into Jupyter by using the Upload button at the top right of your home page. data.txt On your right there is a button titled Upload. Now our data is in Jupyter, all we have to do is to use our stolen code on it! You can grab the notebook which has the code here: https://github.com/zackthoutt/got-book-6/blob/master/got-book-generator.ipynb Either copy paste it or move the whole notebook via the upload command into your Jupyter server. Change the reference in the code to your data book_filenames = sorted(glob.glob("/data/*.txt")) Becomes: book_filenames = sorted(glob.glob("data.txt")) And now you just hit run and go through each of the Cells from top to bottom! Once you train your model (and you can play around with the hyperparameters), you can pick a word and generate a sample of Whitmanesque poetry. It should be saved under an outputs folder on your Jupyter homepage. Here is a sample: i hear the new river-stripes of the western sky,the engulfed wanderings with them throughwhat thou side to the rest, lilacs out at the music, shouting, long, unbereav’d, henceforth in thy task music,here with seed mere purpose more without drop or century enough o people, farther with india!centuries a bunting! always me pleas’d and her time or land!corroborating for the sands of talk and pause toward him,the war wreck’d, the best of hand, then freely alone,endless along the seas,endowoutside aside and his faceof america’s forehead,manhattan in the north as all the golden ground,down through many a distant armies, standing for your brother? Look at that. It makes no sense. But maybe it does? It’s genius is what I say. Now you too can become the next James Joyce and they’ll be trying to figure out what you meant for years to come. Here’s another one: rocks and foam of victory, time and crossing night,however rock the voice andgeneral quickly lovers,we stand no more playing out plan from your aims, libertad,all walk,in the ruins of the two the heroes slowlybusy with her — the odds of the rest prepared,, to its know puts herearound — touch,my comrade at mechanics withwoe,after i at lanes and space beautiful out so well — done now the sun with all their turn there are in last,bright out of the interminable convulsive, journeying, thistheir spheres,for my hands back over the white hand in a swamp,i know as feudal voice, inseparably coarse and round hand is so,till i hear the carol wash’d cubic instruments, and bear close its hoarse steps in the frozen sentry,the builder, corner’d and desperate, an creatures,the shy and odour to, the sailors the arrogant small, and ringing the splashing rolls whirl sat,out and the real cover years overhead rising or tumbling city. Doesn’t it bring a tear to your eye? Also, if your model is taking a long time to run please make sure you are running it on your GPU. You can check this by running: nvidia-smi If it shows a message of No Running Process, even though your model is being trained, it means the GPU has not been hooked up properly. Again, make sure you ran this line: export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64 Hope this was helpful! Please do share your results. I’d be curious to see what you got. :) Bilal

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