DEV Community: Fredy Somy

Automate Build and deploy of Python Package using Github actions.

Fredy Somy — Sat, 13 Feb 2021 08:12:25 +0000

Are you tired of manually building and deploying Python packages to PyPi. Well here is the solution.

What you need.

A github account
A PyPi account.
A Packagable Python project.
- if you dont know how to package a project refer here

Lets get started

Go to the repo containing your python project.
Click on Actions tab. A window appears.
Select the Publish Python package action.
Notice that the new file which we are commiting is in the .github folder and inside the workflows folder.

.github/workflows/python-publish.yml

Lets see the code which is .yml file containing some commands to be excecuted .

name: Upload Python Package

on:
  release:
    types: [created]

jobs:
  deploy:

    runs-on: ubuntu-latest

    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.x'
    - name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        pip install setuptools wheel twine
    - name: Build and publish
      env:
        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
      run: |
        python setup.py sdist bdist_wheel
        twine upload dist/*

Let me explain Line by line.

name: Upload Python Package

on:
  release:
    types: [created]

The name : " " is the name of the workflow which you are creating.
The "on" depicts a event which here is the releases event.
If we want to run the workflow each time we push code .👇

on:
  push:
    branches : [ master ]

Here the event is "Push" so each time you push code the workflow runs.

jobs:
 .....

Jobs tells the workflow what all jobs have to be done when the workflow is triggered.

deploy:
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: '3.x'

runs-on specifies which OS it should run on.
Then the steps is a long list of works to be done.
Here the first job is to set up python and the - name means the name of the job running.
Here is a set of jobs running in my package.
Then after setting up python we have to install the dependencies.

- name: Install dependencies
      run: |
        python -m pip install --upgrade pip
        python -m pip install -r requirements.txt
        pip install setuptools wheel twine

Here the run: | is the set of commands to be executed.
- We are Upgrading pip.
- Installing the dependencies in requirements.txt
- And we are installing setuptools , wheel and twine.
setuptools and wheel are for packaging.
Twine is for uploading the package to Pypi.
Here is the final part to Build and Publish a package.

- name: Build and publish
      env:
        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
      run: |
        python setup.py sdist bdist_wheel
        twine upload dist/*

The env: is some environment variables which you need ( Here your PyPi username and password.)
- You can go to the repo settings and add secrets , which can be accessed by secrets.envname

In the "run :" you are seeing two commands.
- Here python setup.py sdist bdist_wheel builds the package and add it into a dist/ folder.
And finally " twine upload dist/* " uploads the distributions to PyPi.
You can also set up tests if you want.

Contact

Feel free to email me for Bugs Found or queries.
- Twitter
- Linkedin
I will be happy to help.
Cover image taken from here

How to Route using Subdomain in React.

Fredy Somy — Sat, 23 Jan 2021 18:02:03 +0000

When i was making my portfolio in React , i wanted to have all components in different subdomains.

Eg :

My domain : https://fredy.rocks/ ,

I want my Projects component at https://projects.fredy.rocks/,

My blog at https://blog.fredy.rocks/ and more..
I really wanted to do that , but i found nothing.
After asking some of my seniors i finally did it with conditional component rendering .

It means if a url is having a specific subdomain , the component ( which we have assigned for the subdomain) should be rendered.

Code

We all know the Web API's .
Lets use window.location API

if (window.location.host.split('.')[0] == 'projects' 
{
console.log("projects component")
}

Well this is the core idea i am using.

What is window.location

>>console.log(window.location)
>>
{hash: ""
host: "projects.fredy.rocks"
hostname: "projects.fredy.rocks"
href: "https://projects.fredy.rocks/"
origin: "https://projects.fredy.rocks"
pathname: "/"
port: ""
protocol: "https:"}

So window.location gives us the details about the current website url and other stuffs like hostname,href,pathname,protocol etc.

Our goal is to find the subdomain in the url.

>> console.log(window.location.host)
>> projects.fredy.rocks
// Here we get the host of the website and the subdomain can be extracted after spliting the above result.
>> console.log(window.location.host.split('.')[0])
>> projects
// Yes we got the subdomain after spliting the host and getting its 0th index which in here is the subdomain name.

Lets get back to React.

Lets do some basic react stuffs after using CRA template.

import Projects from "./projects/Projects";
// Projects is the component i want to render 
import { BrowserRouter as Router, Switch, Route } from "react-router-dom";
// If you are using react router inside the component better wrap the component in </Router>

function App() {
  if (window.location.host.split(".")[0] == "projects") {
// It checks if the subdomain is named projects.
    return (
      <Router>
        <Header />
        <Projects />
      </Router>
    );
  }

export default App;
// Exporting App

That's the whole code needed to setup a subdomain based router in react.

You can add a else block and render a Error page if needed.

Contact

Feel free to email me for Bugs Found or queries.
- Twitter
- Linkedin
I will be happy to help.
Cover image taken from here

MarkdownIt - A Comprehensive Guide.

Fredy Somy — Fri, 18 Dec 2020 01:32:59 +0000

MarkdownIt-Guide

A Efficent Code Editor to live render Markdown and Can save the rendered file as Markdown,Html and Pdf.Also Instant Hosting for static single paged websites.

Editor

The left window is the editor where you can edit the markdown.
The right window live previews the changes you made in the editor.

The SAVE AS button allows you to save your .md files.
With OPEN FILE you can open any .md files to edit.
SAVE AS PDF allows you to convert the markdown you wrote in editor to pdf.
SAVE AS HTML allows you to convert the markdown you wrote in editor to html format.
Settings button gives you access to change theme of editor.

Settings

You can change the theme of the editor to various themes available.
You can also change the background and text color.( Refer image above ).

MarkdownItHost

Web hosting service inside MarkdownIt.

You can create a new website with the CREATE SITE button.
Instant publishing can be done using PUBLISH button.
You can edit any websites you made (provided you have the config file for the respective website in your system).

For more explanation watch the gif below.

Click here to see the gif.

Contact

Feel free to email me for Bugs Found or queries.
- Twitter
- Linkedin
I will be happy to help.

MarkdownIt - A Code Editor to render Markdown and host it.

Fredy Somy — Thu, 17 Dec 2020 17:09:02 +0000

Efficent Code Editor to live render Markdown and Can save the rendered file as Markdown,Html and Pdf . Also Instant Hosting in The Web.

Features • MarkdownItHost • Downloads • Guide

fredysomy / MarkdownIt

Efficient Code Editor to live render Markdown and save as Markdown,Html and Pdf with Instant Hosting in The Web.

Features

Live preview of the changes you make
You can save the file and open any md files in the editor.
You can save convert the markdown you have written into html and pdf.
Uses Ace editor
Bootstrap styling is enabled
You can change the editor themes and text colors for your preference
- There is a settings.json file to handle all themes and style changes
Html tags can be used with the markdown.
- The pdf file generated is also html friendly.
Clean UI and also have a reference for markdown.
Has instant web hosting feature.
- You can create a static single paged website in this editor.
- MarkdownItHost is the service in the editor that allows you to host websites.

MarkdownItHost

A simple way to host websites (included in the code editor)
One can create a webpage with one click See here
A config file with the path name of your website and unique secret id is to be saved in your PC.
Only with the config file you can edit and publish your site.
Deploys a Static website within 2 seconds.(With 2-3 clicks).
Any bugs or queries can be mailed to me
All the "HOW to" guide is included Here
You can use Bootstrap styling inside the code you Write ( no need to inculde the scripts)

How to use(Source code)

Clone this repository

 git clone https://github.com/fredysomy/MarkdownIt

Install dependencies

 npm install

Run the app

 npm start

Changelog

`v1.0.0`

Added code editor
Added file saving
Aditional options like save as pdf and save as html.

`v1.0.2`

Added MarkdownItHost to publish static websites
Online offline alerts.

Contibute

Fork the repostory
install the dependencies
Make your changes
And make a pull request from your repo. (I will surely look forward for the PR's)

Made with

Electron
Ace js
markdown-pdf

Scrape Github User details with Python.

Fredy Somy — Sun, 13 Dec 2020 09:33:41 +0000

When i was learning web scraping , one of the ideas that came to my mind is a Github Scraper.
Here i will try my best to describe each process.

Lets start..

We have to install a couple of packages first.

Beautifulsoup
requests
htmlparser

pip install requests
pip install html5lib
pip install beautifulsoup4

Then open https://github.com/yourusername
Open Devtools.
This is what i see when i open my dashboard and devtools.
While we scrape web , we need the element's id ,classname or xpath to scrape it.
We will be scraping Name, Username , No of Repos, Followers , Following and profile image.

import requests
from bs4 import BeautifulSoup
import html5lib

Import the modules.

r=requests.get("https://github.com/fredysomy")
soup=BeautifulSoup(r.content,'html5lib')

Make a request into the website.
Parse the html recieved as response in r.content using beautifulsoup and html5lib.
From here we are starting scraping.

namediv=soup.find("h1" ,class_="vcard-names pl-2 pl-md-0")
name=namediv.find_all('span')[0].getText()
u_name=namediv.find_all('span')[1].getText()

Here we are getting all element in the element of class name vcard-names pl-2 pl-md-0"
Name and Username are in the span element in the above div.
We have assigned the content into namediv variable.
We are finding all span elements and selecting (0:name,1:Username) and getting the text using getText() function.

statstab=soup.find(class_="flex-order-1 flex-md-order-none mt-2 mt-md-0")
elements=statstab.find(class_="mb-3")
followers=elements.find_all('a')[0].find('span').getText().strip(' ')
following=elements.find_all('a')[1].find('span').getText().strip(' ')
totstars=elements.find_all('a')[2].find('span').getText().strip(' ')

Here the same thing happens.
Followers,Following,Stargazers are inside element of classname flex-order-1 flex-md-order-none mt-2 mt-md-0 and in mb-3 which is inside that.
Lets get that and store it in elements variable.
Getting the span inside inside the elements returns a list.
- Followers is having index=0
- Following is having index=1
- Stargazer is having index=2

elements.find_all('a')[2].find('span').getText().strip(' ')

Here we are getting the second index item in a element and then getText() from the span inside it. We are using strip('') to remove unneccesary blank spaces in the result.

u_img=soup.find(class_="avatar avatar-user width-full border bg-white")['src']

The above code gives the image tag and we are getting the src attribute.

repo_num=soup.find(class_="UnderlineNav-body").find('span',class_="Counter").getText()

Here we are getting the no of repos user haves.
That is all you need to scrape user details with python.

Source Code

import requests
from bs4 import BeautifulSoup
import html5lib
r=requests.get("https://github.com/fredysomy")
soup=BeautifulSoup(r.content,'html5lib')
namediv=soup.find("h1" ,class_="vcard-names pl-2 pl-md-0")
name=namediv.find_all('span')[0].getText()
u_name=namediv.find_all('span')[1].getText()
statstab=soup.find(class_="flex-order-1 flex-md-order-none mt-2 mt-md-0")
elements=statstab.find(class_="mb-3")
followers=elements.find_all('a')[0].find('span').getText().strip(' ')
following=elements.find_all('a')[1].find('span').getText().strip(' ')
totstars=elements.find_all('a')[2].find('span').getText().strip(' ')
u_img=soup.find(class_="avatar avatar-user width-full border bg-white")['src']
repo_num=soup.find(class_="UnderlineNav-body").find('span',class_="Counter").getText()

The idea is that, we should make the program to navigate to the element we want and select the required element.
Refer some beautifulsoup methods here
I have also made a pypi module to scrape Github.See it here and give a star if you like it.

If you have any doubts or need clarification, comment down below.

Stay tuned for part 2 where we will scrape the user repo details.

Hunt some strange numbers with Python.

Fredy Somy — Thu, 10 Dec 2020 16:49:10 +0000

We have heard about Different types of numbers and series.
For example Ramanujan Number, is the smallest number which can be expressed as the sum of two different cubes in two different ways.

Today we are going to see some another strange types of numbers and how to generate it with Python.

How strange!

Lets take a look at this number ..
The number 2520 looks like a normal number like other numbers, but it is not like that.
The strange thing is that it is divisible by numbers from 1 to 10, whether these numbers are odd or even !!

Lets see:

2520 ÷ 1 = 2520
2520 ÷ 2 = 1260
2520 ÷ 3 = 840
2520 ÷ 4 = 630
2520 ÷ 5 = 504
2520 ÷ 6 = 420
2520 ÷ 7 = 360
2520 ÷ 8 = 315
2520 ÷ 9 = 280
2520 ÷ 10 = 252

See its awesome... But there is many more numbers like that.
Example: 5040,7560

Lets find more numbers like this by the way we Programmers do ..
We are going to do it Programmatically with Python 🐍

Lets get started.

Aim:

Find numbers which are divisible by numbers from 1-10

Code:

def check(id: int):
    for i in range(1,id):
        check= 0
        for j in range(1,11):
            if i%j==0:
                check= check+1
        if check==10:
            print(i)


check(100000)

The Code is simple.

We are getting numbers from 1-100000(here) using for loop and range.
We are initialising a variable to check for divisibility.

check=0
for j in range(1,11):
    if i%j==0:
        check= check+1
if check==10:
     print(i)

In the for loop we are checking the divisibility of the number with each numbers from 1-10.
If a number is divisible the it will increment check by 1.
Finaly we check if variable check is equal to 10 ( Means that the numbers is divisible by each in 1-10)

Final Output:

2520
5040
7560
10080
12600
15120
17640
20160
22680
25200
27720
30240
32760
35280
37800
40320
42840                                         45360
47880
50400
52920                                         55440
57960
60480
63000
65520
68040
70560
73080
75600
78120
80640
83160
85680
88200
90720
93240
95760
98280

That is for today guys .Thanks for reading the blog.

How to encode and store images in PysonDB.

Fredy Somy — Fri, 04 Dec 2020 19:14:18 +0000

Many of us find it difficult to add image to a database. PysonDB solves most of your problems now i will be showing how to store image in PysonDB

What are we doing today:

We are going to encode a image and then decode it.
Then we are going to store it in PysonDB.

Prerequisites

Install pysondb via pip

pip install pysondb

Lets get started.

We are having a image as below.

file2son.png

We are going to encode it.

We need to import base64 module first.
It handles the base64 encoding of image.

from pysondb import db 
import base64
from PIL import Image
from io import BytesIO

x=db.getDb("fs.json")
def addimage(fi,name):
  with open(fi,"rb") as dataimg:
    raw_data=base64.b64encode(dataimg.read())
    x.add({"data":raw_data.decode('utf-8'),"name":name})

addimage("file2son.png","image12")

We are importing pysondb,bas64
Other two will be handled soon.

x=db.getDb("fs.json")

This creates or connects a Json database named fs.json
If you dont know pysonDB read this

def addimage(fi,name):
  with open(fi,"rb") as dataimg:
    raw_data=base64.b64encode(dataimg.read())
    x.add({"data":raw_data.decode('utf-8'),"name":name})

addimage("file2son.png","image12")

We are opening a file ( here file2son.png ) in read,binary mode as dataimg.

raw_data=base64.b64encode(dataimg.read())

This encodes all data in dataimg in base64 format.

 x.add({"data":raw_data.decode('utf-8'),"name":name})

This piece of code stores data in pysondb database .
See that the raw_data after encoding is decoded in 'utf-8' format.
Else error is shown.

So finally we have the data in fs.json database.

Lets get back the image

def getimage(filename,name):
  img_data=x.getBy({"name":name})
  img=Image.open(BytesIO(base64.b64decode(img_data[0]['data2'])))
  img.save(filename,"PNG")

getimage("file.png","image12")

img_data=x.getBy({"name":name})

This piece of code gets the base64 data from fs.json with the provided name.

img=Image.open(BytesIO(base64.b64decode(img_data[0]['data2'])))

Here we are Using Image from pillow (PIL) module.
What this code does is:
- Opens the base64 data from fs.json
- And BytesIO converts the data into a byte stream which is caught by the Image function and assigned to img variable.

img.save(filename,"PNG")

This saves the img in filename (here file.png ) in PNG format
You have file.png in the directory which was encoded and decoded.

Whole Code

from pysondb import db
import base64
from PIL import Image
from io import BytesIO

x=db.getDb("fs.json")
def addimage(fi,name):
  with open(fi,"rb") as data:
    raw_data=base64.b64encode(data.read())
    x.add({"data":raw_data.decode('utf-8'),"name":name})


addimage("file2son.png","image12")
# addimage() is used to add file2son.png image in database with name as image12

def getimage(filename,name):
  img_data=x.getBy({"name":name})
  img=img_data[0]['data2'].decode('base64'))
  img.save(filename,"PNG")
getimage("file.png","image12")
# getimage is used to retrieve the stored image of name image12 and get it as file.png

Thats for today,Follow for more blogs.

Have any doubts or am i wrong anywhere,please comment here. So that i can correct it.

Transfer Data from CSV files to Deta Bases + Alternative solution.

Fredy Somy — Fri, 04 Dec 2020 04:20:04 +0000

What are we going to do.

First of all , lets go through this in two phases.

Convert csv to json
Upload converted json to Deta base

Prerequisites

Create a free account in Deta
Create a new project (Note down the project key, we need it)

Lets start.

Imagine having a csv file as

name,age
fredy,34
god,34345345
mannu,34

We want it like:

[{'name': 'fredy', 'age': '34'},{'name': 'god', 'age': '34345345'}
,{'name': 'maanu', 'age': '34'}
]

Lets start by importing csv module

import csv

Read the file contents:

arr=[]
with open (path) as csvFile:
    csvReader = csv.DictReader(csvFile)
    for csvRow in csvReader:
        arr.append(csvRow)

We are making a list named arr for appending all the json extracted from csv.

csvReader = csv.DictReader(csvFile)

This creates a csvreader object which maps each row to a dictionary.
We can now use the csvreader to extract the dictionary.

for csvRow in csvReader:
      arr.append(csvRow)

The above loop takes each dictionary from csvreader object and append it to list arr,which i mentioned earlier.
We can now print the list arr to see the json data.

>> print(arr)
[{'name': 'fredy', 'age': '34'},{'name': 'god', 'age': '34345345'}
,{'name': 'maanu', 'age': '34'}
]

Csv file is converted , lets upload it to Deta Base

Install deta module.

pip install deta

Lets import it.

from deta import Deta

Initialize with a Project Key( which we get while creating a project)

deta = Deta(projectkey)
database = deta.Base(db)
for each in arr:
    datafile.insert(each)
    print("Uploaded {}".format(each))

Connect or create a database in Deta

database = deta.Base(db)

for each in arr:
    datafile.insert(each)
    print("Uploaded {}".format(each))

We are iterating through the list arr and datafile.insert(each) inserts each data into the database.
Finally we have this in Deta Base UI.

Final Code

def csvtodeta(id,path,db):
    deta = Deta(id)
    datafile = deta.Base(db)
    print("Reading data from {}".format(path))
    arr=[]
    with open (path) as csvFile:
        csvReader = csv.DictReader(csvFile)
        for csvRow in csvReader:
           arr.append(csvRow)
    for each in arr:
        datafile.insert(each)
        print("Uploaded {}".format(each))
    print("succesfully uploaded {} data to {} Base".format(len(arr),db))

Alternative Solution

I created a python CLI tool to do the same.

pip install csvtodeta

With just one command the data of csv file is uploaded to Deta🎉.

$ csvtodeta --id yourprojectkey --path path/to/csv.csv --db detabasename

id is your project key from deta
Provide the path name of csv file.
Provide database name of the Base you want to create or connect.
Tada...🎉🎉 The data is uploaded.

$ csvtodeta --id 45345dhsgh3rjdf2ur34hhwf --path src/deta.csv --db detabasename
Reading data from src/deta.csv
Uploaded {'name': 'fredy', 'age': '34'}
Uploaded {'name': 'god', 'age': '34345345'}
Uploaded {'name': 'maanu', 'age': '34'}
succesfully uploaded 3 data to detabasename Base

Github Repo

Thank you for reading this blog. If you have any doubts or if there is any wrong explanation please comment down here.

PysonDB - A JSON based lightweight Database for Python.

Fredy Somy — Tue, 01 Dec 2020 18:26:04 +0000

Features

Lightweight JSON based database.
Supports CRUD commands.
No Database drivers required.
Unique ID assigned for each JSON document added.
Strict about Schema of data added.
Inbuilt CLI to delete,display,create JSON database.
Convert CSV files to JSON file to use in pysonDB

>> from pysondb import db
>> a=db.getDb("path/to/json.json")
>> a.addMany([{"name":"pysondb","type":"DB"},{"name":"pysondb-cli","type":"CLI"}])
>> a.getAll()
>> [{"name":"pysondb","type":"DB"},{"name":"pysondb-cli","type":"CLI"}]

See its simple..

Join Discord server here

Github Repo

Give it a Star if you like this project.

Install

pip install pysondb

Create a database

You can create a database using CLI.

pysondb create database_name

Or in the python file.

from pysondb import db

a=db.getDb("db.json')

The above piece of code will create a database with {data:[]} in it.
Even if the json file exists there is no problem.

Add data.

There are two methods to add data.
add({})

>> from pysondb import db
>> a=db.getDb("pathtojson.json")
>> a.add({"name":"pysondb","type":"DB"})
>> # returns 1929323232 which is a ID assigned to the above data.
>> a.add({"namme":"pyson","type":"DB"})
>> # The data wont be added as the key "name" is mispelled as "namme"

addMany([{},{}....])

>> from pysondb import db
>> a=db.getDb("pathtojson.json")
>> a.addMany([{"name":"pysondb","type":"DB"},{"name":"py_cli","type":"CLI"}])
>> # Both data is added in the database.
>> a.addMany([{"namme":"pyson","type":"DB"},{"name":"py_cli2","type":"CLI"}])

>> # The first data wont be added as the key "name" is mispelled as "namme"
>> # But the second data will be added.

Get Data

returns only one data by default.
get(3) => retruns 3 json data.

path.json

{"data":[{"name":"pysondb","type":"DB"},{"name":"py_cli","type":"CLI"},{"name":"py_cli2","type":"CLI"}]}

`get(n)`

>> from pysondb import db
>> a=db.getDb("path.json")
>> a.get()
>> [{"name":"pysondb","type":"DB"}]
>> a.get(2)
>> [{"name":"pysondb","type":"DB"},{"name":"py_cli","type":"CLI"}]

`getAll()`

Returns all data in the database

>> from pysondb import db
>> a=db.getDb("path.json")
>> a.getAll()
>> [{"name":"pysondb","type":"DB"},{"name":"py_cli","type":"CLI"},{"name":"py_cli2","type":"CLI"}]

`getBy(query)`

getBy(query) query must be a JSON data.
getBy({"type":"CLI"})

>> from pysondb import db
>> a=db.getDb("path.json")
>> a.getBy({"type":"CLI"})
>> [{"name":"py_cli","type":"CLI"},{"name":"py_cli2","type":"CLI"}]
>> a.getBy({"name":"py_cli"})
>> [{"name":"py_cli","type":"CLI"}]

Update Data

JSON file:file.json

{"data": [{"name": "PysonDB", "type": "DB", "score": "10", "id": 5161221802},
{"name": "Pyson-CLI", "type": "CLI", "score": "10", "id": 2242313690},
{"name": "Tiny", "type": "DB", "score": "9", "id": 6991190264},
{"name": "QWERTY", "type": "DB", "score": "5", "id": 9416036202}]}

`updateById(ID,what_to_update)`

ID=Integer

>> from pysondb import db
>> a=db.getDb("file.json")
>> a.updateById("9416036202",{"name":"Qwerty12"})

>> #In the file.json the data is updated.
>> #We can verify it below.
>> a.getBy({"name":"Qwerty12"})
>> [{"name": "Qwerty12", "type": "DB", "score": "5", "id": 9416036202}]

`update(query,what_to_update)`

query,what_to_update are both JSON data.

>> from pysondb import db
>> a=db.getDb("file.json")
>> a.update({"name":"Pyson-CLI"},{"name":"PysonCLI"})

>> # In the file.json the data is updated for all data where name=Pyson-CLI
>> # We can verify it below.
>> a.getBy({"name":"PysonCLI"})
>> [{"name": "PysonCLI", "type": "CLI", "score": "10", "id": 2242313690}]

Delete Data

`deleteById(ID)`

file.json is same as the above

>> from pysondb import db
>> a=db.getDb("file.json")
>> a.deleteById("6991190264")
>> # The JSON data with ID "6991190264" is deleted.Lets verify.
>> a.getAll()
>> [{"name": "PysonDB", "type": "DB", "score": "10", "id": 5161221802},
{"name": "Pyson-CLI", "type": "CLI", "score": "10", "id": 2242313690},
{"name": "QWERTY", "type": "DB", "score": "5", "id": 9416036202}]

CLI operations

Use

`pysondb convert --c [csv file destination] --d [json file to write]`

C:\Users\Admin\Desktop\pysondb>pysondb convert --c file.csv --d file.json
Reading data from file.csv
Writing data into file.json
Conversion Succesfull

`pysondb create [name]`

C:\Users\Admin\Desktop\pysondb>pysondb create filedb.json
Succesfull created filedb.json in the directory.

`pysondb delete [name]`

C:\Users\Admin\Desktop\pysondb>pysondb delete file2.json
Do you want to remove the json file..(y/n)y
File deleted.

C:\Users\Admin\Desktop\pysondb>pysondb delete filedb.json
Do you want to remove the json file..(y/n)n
Action terminated

`pysondb display [name]`

File: filedb.json

{"data": [{"name": "PysonDB", "type": "DB", "score": "10", "id": 5161221802}, {"name": "Pyson-CLI", "type": "CLI", "score": "10", "id": 2242313690}, {"name": "TinyDb", "type": "DB", "score": "9", "id": 6991190264}, {"name": "QWERTY", "type": "DB", "score": "5", "id": 9416036202}]}

Code.

C:\Users\Admin\Desktop\pysondb>pysondb display filedb.json
+-----------+------+-------+------------+
|   name    | type | score |     id     |
+-----------+------+-------+------------+
|  PysonDB  |  DB  |  10   | 5161221802 |
+-----------+------+-------+------------+
| Pyson-CLI | CLI  |  10   | 2242313690 |
+-----------+------+-------+------------+
|   Tiny    |  DB  |   9   | 6991190264 |
+-----------+------+-------+------------+
|  QWERTY   |  DB  |   5   | 9416036202 |
+-----------+------+-------+------------+

What makes pysonDB different

CLI support to create,delete and display database.
Unique Id automatically assigned for each JSON data added.
Schema regularity is checked.

What pysonDB can't do.

Cannot store images,videos etc.

DEV Community: Fredy Somy

Automate Build and deploy of Python Package using Github actions.

What you need.

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How to Route using Subdomain in React.

When i was making my portfolio in React , i wanted to have all components in different subdomains.

Eg :

My domain : https://fredy.rocks/ ,

Code

What is window.location

Lets get back to React.

Contact

MarkdownIt - A Comprehensive Guide.

MarkdownIt-Guide

Editor

Settings

MarkdownItHost

Web hosting service inside MarkdownIt.

For more explanation watch the gif below.

Contact

MarkdownIt - A Code Editor to render Markdown and host it.

fredysomy / MarkdownIt

Efficient Code Editor to live render Markdown and save as Markdown,Html and Pdf with Instant Hosting in The Web.

Features

MarkdownItHost

How to use(Source code)

Clone this repository

Install dependencies

Run the app

Changelog

v1.0.0

v1.0.2

Contibute

Made with

Scrape Github User details with Python.

Lets start..

Source Code

Hunt some strange numbers with Python.

How strange!

Lets see:

Lets get started.

How to encode and store images in PysonDB.

What are we doing today:

Prerequisites

Lets get started.

Lets get back the image

Whole Code

Thats for today,Follow for more blogs.

Have any doubts or am i wrong anywhere,please comment here. So that i can correct it.

Transfer Data from CSV files to Deta Bases + Alternative solution.

What are we going to do.

Prerequisites

Lets start.

Lets start by importing csv module

Csv file is converted , lets upload it to Deta Base

Final Code

Alternative Solution

Github Repo

Thank you for reading this blog. If you have any doubts or if there is any wrong explanation please comment down here.

PysonDB - A JSON based lightweight Database for Python.

Features

Join Discord server here

Github Repo

Give it a Star if you like this project.

Install

Create a database

Add data.

Get Data

get(n)

getAll()

getBy(query)

Update Data

updateById(ID,what_to_update)

update(query,what_to_update)

Delete Data

deleteById(ID)

CLI operations

Use

pysondb convert --c [csv file destination] --d [json file to write]

`v1.0.0`

`v1.0.2`

`get(n)`

`getAll()`

`getBy(query)`

`updateById(ID,what_to_update)`

`update(query,what_to_update)`

`deleteById(ID)`

`pysondb convert --c [csv file destination] --d [json file to write]`

`pysondb create [name]`

`pysondb delete [name]`

`pysondb display [name]`