1602483166
In this video you’ll learn how to create a Read More component in Angular. This component is very useful specially when you have a long text and you want to shorten it by expanding and collapsing the component.
Here is the github url for the app source code used as demo in this video:
https://github.com/festackcode/read-more-component
The font awesome package I used in the demo app is here:
https://github.com/FortAwesome/angular-fontawesome
https://www.youtube.com/watch?v=7OIImBVZjn0
#angular #component #typescript
1655630160
Install via pip:
$ pip install pytumblr
Install from source:
$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install
A pytumblr.TumblrRestClient
is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:
client = pytumblr.TumblrRestClient(
'<consumer_key>',
'<consumer_secret>',
'<oauth_token>',
'<oauth_secret>',
)
client.info() # Grabs the current user information
Two easy ways to get your credentials to are:
interactive_console.py
tool (if you already have a consumer key & secret)client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user
client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog
client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post
client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog
Creating posts
PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.
The default supported types are described below.
We'll show examples throughout of these default examples while showcasing all the specific post types.
Creating a photo post
Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload
#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")
#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
tweet="Woah this is an incredible sweet post [URL]",
data="/Users/johnb/path/to/my/image.jpg")
#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
caption="## Mega sweet kittens")
Creating a text post
Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html
#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")
Creating a quote post
Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported
#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")
Creating a link post
#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
description="Search is pretty cool when a duck does it.")
Creating a chat post
Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)
#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])
Creating an audio post
Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr
#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")
#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")
Creating a video post
Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload
#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
embed="http://www.youtube.com/watch?v=40pUYLacrj4")
#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")
Editing a post
Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.
client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")
Reblogging a Post
Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.
client.reblog(blogName, id=125356, reblog_key="reblog_key")
Deleting a post
Deleting just requires that you own the post and have the post id
client.delete_post(blogName, 123456) # Deletes your post :(
A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):
client.create_text(blogName, tags=['hello', 'world'], ...)
Getting notes for a post
In order to get the notes for a post, you need to have the post id and the blog that it is on.
data = client.notes(blogName, id='123456')
The results include a timestamp you can use to make future calls.
data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])
# get posts with a given tag
client.tagged(tag, **params)
This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).
You'll need pyyaml
installed to run it, but then it's just:
$ python interactive-console.py
and away you go! Tokens are stored in ~/.tumblr
and are also shared by other Tumblr API clients like the Ruby client.
The tests (and coverage reports) are run with nose, like this:
python setup.py test
Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license
1598940617
Angular is a TypeScript based framework that works in synchronization with HTML, CSS, and JavaScript. To work with angular, domain knowledge of these 3 is required.
In this article, you will get to know about the Angular Environment setup process. After reading this article, you will be able to install, setup, create, and launch your own application in Angular. So let’s start!!!
For Installing Angular on your Machine, there are 2 prerequisites:
First you need to have Node.js installed as Angular require current, active LTS or maintenance LTS version of Node.js
Download and Install Node.js version suitable for your machine’s operating system.
Angular, Angular CLI and Angular applications are dependent on npm packages. By installing Node.js, you have automatically installed the npm Package manager which will be the base for installing angular in your system. To check the presence of npm client and Angular version check of npm client, run this command:
· After executing the command, Angular CLI will get installed within some time. You can check it using the following command
Now as your Angular CLI is installed, you need to create a workspace to work upon your application. Methods for it are:
To create a workspace:
#angular tutorials #angular cli install #angular environment setup #angular version check #download angular #install angular #install angular cli
1591081592
Learn how to create and consume a custom component harness using Angular CDK. With a step-by-step case study, we run it in unit tests and end-to-end tests.
Updated for Angular CDK and Angular Material version 9.2.
A component harness is a testing API around an Angular directive or component. Component harnesses can be shared between unit tests, integration tests, and end-to-end tests. They result in less brittle tests as implementation details are hidden from test suites.
#angular #angular-cdk #component-harnesses #testing #angular-material
1593184320
What is Angular? What it does? How we implement it in a project? So, here are some basics of angular to let you learn more about angular.
Angular is a Typescript-based open-source front-end web application platform. The Angular Team at Google and a community of individuals and corporations lead it. Angular lets you extend HTML’s syntax to express your apps’ components clearly. The angular resolves challenges while developing a single page and cross-platform applications. So, here the meaning of the single-page applications in angular is that the index.html file serves the app. And, the index.html file links other files to it.
We build angular applications with basic concepts which are NgModules. It provides a compilation context for components. At the beginning of an angular project, the command-line interface provides a built-in component which is the root component. But, NgModule can add a number of additional components. These can be created through a template or loaded from a router. This is what a compilation context about.
Components are key features in Angular. It controls a patch of the screen called a view. A couple of components that we create on our own helps to build a whole application. In the end, the root component or the app component holds our entire application. The component has its business logic that it does to support the view inside the class. The class interacts with the view through an API of properties and methods. All the components added by us in the application are not linked to the index.html. But, they link to the app.component.html through the selectors. A component can be a component and not only a typescript class by adding a decorator @Component. Then, for further access, a class can import it. The decorator contains some metadata like selector, template, and style. Here’s an example of how a component decorator looks like:
@Component({
selector: 'app-root',
templateUrl: 'app.component.html',
styleUrls: ['app.component.scss']
})
Modules are the package of functionalities of our app. It gives Angular the information about which features does my app has and what feature it uses. It is an empty Typescript class, but we transform it by adding a decorator @NgModule. So, we have four properties that we set up on the object pass to @NgModule. The four properties are declarations, imports, providers, and bootstrap. All the built-in new components add up to the declarations array in @NgModule.
@NgModule({
declarations: [
AppComponent,
],
imports: [
BrowserModule,
HttpClientModule,
AppRoutingModule,
FormsModule
],
bootstrap: [AppComponent]
})
Data Binding is the communication between the Typescript code of the component and the template. So, we have different kinds of data binding given below:
#angular #javascript #tech blogs #user interface (ui) #angular #angular fundamentals #angular tutorial #basics of angular
1657081614
In this article, We will show how we can use python to automate Excel . A useful Python library is Openpyxl which we will learn to do Excel Automation
Openpyxl is a Python library that is used to read from an Excel file or write to an Excel file. Data scientists use Openpyxl for data analysis, data copying, data mining, drawing charts, styling sheets, adding formulas, and more.
Workbook: A spreadsheet is represented as a workbook in openpyxl. A workbook consists of one or more sheets.
Sheet: A sheet is a single page composed of cells for organizing data.
Cell: The intersection of a row and a column is called a cell. Usually represented by A1, B5, etc.
Row: A row is a horizontal line represented by a number (1,2, etc.).
Column: A column is a vertical line represented by a capital letter (A, B, etc.).
Openpyxl can be installed using the pip command and it is recommended to install it in a virtual environment.
pip install openpyxl
We start by creating a new spreadsheet, which is called a workbook in Openpyxl. We import the workbook module from Openpyxl and use the function Workbook()
which creates a new workbook.
from openpyxl
import Workbook
#creates a new workbook
wb = Workbook()
#Gets the first active worksheet
ws = wb.active
#creating new worksheets by using the create_sheet method
ws1 = wb.create_sheet("sheet1", 0) #inserts at first position
ws2 = wb.create_sheet("sheet2") #inserts at last position
ws3 = wb.create_sheet("sheet3", -1) #inserts at penultimate position
#Renaming the sheet
ws.title = "Example"
#save the workbook
wb.save(filename = "example.xlsx")
We load the file using the function load_Workbook()
which takes the filename as an argument. The file must be saved in the same working directory.
#loading a workbook
wb = openpyxl.load_workbook("example.xlsx")
#getting sheet names
wb.sheetnames
result = ['sheet1', 'Sheet', 'sheet3', 'sheet2']
#getting a particular sheet
sheet1 = wb["sheet2"]
#getting sheet title
sheet1.title
result = 'sheet2'
#Getting the active sheet
sheetactive = wb.active
result = 'sheet1'
#get a cell from the sheet
sheet1["A1"] <
Cell 'Sheet1'.A1 >
#get the cell value
ws["A1"].value 'Segment'
#accessing cell using row and column and assigning a value
d = ws.cell(row = 4, column = 2, value = 10)
d.value
10
#looping through each row and column
for x in range(1, 5):
for y in range(1, 5):
print(x, y, ws.cell(row = x, column = y)
.value)
#getting the highest row number
ws.max_row
701
#getting the highest column number
ws.max_column
19
There are two functions for iterating through rows and columns.
Iter_rows() => returns the rows
Iter_cols() => returns the columns {
min_row = 4, max_row = 5, min_col = 2, max_col = 5
} => This can be used to set the boundaries
for any iteration.
Example:
#iterating rows
for row in ws.iter_rows(min_row = 2, max_col = 3, max_row = 3):
for cell in row:
print(cell) <
Cell 'Sheet1'.A2 >
<
Cell 'Sheet1'.B2 >
<
Cell 'Sheet1'.C2 >
<
Cell 'Sheet1'.A3 >
<
Cell 'Sheet1'.B3 >
<
Cell 'Sheet1'.C3 >
#iterating columns
for col in ws.iter_cols(min_row = 2, max_col = 3, max_row = 3):
for cell in col:
print(cell) <
Cell 'Sheet1'.A2 >
<
Cell 'Sheet1'.A3 >
<
Cell 'Sheet1'.B2 >
<
Cell 'Sheet1'.B3 >
<
Cell 'Sheet1'.C2 >
<
Cell 'Sheet1'.C3 >
To get all the rows of the worksheet we use the method worksheet.rows and to get all the columns of the worksheet we use the method worksheet.columns. Similarly, to iterate only through the values we use the method worksheet.values.
Example:
for row in ws.values:
for value in row:
print(value)
Writing to a workbook can be done in many ways such as adding a formula, adding charts, images, updating cell values, inserting rows and columns, etc… We will discuss each of these with an example.
#creates a new workbook
wb = openpyxl.Workbook()
#saving the workbook
wb.save("new.xlsx")
#creating a new sheet
ws1 = wb.create_sheet(title = "sheet 2")
#creating a new sheet at index 0
ws2 = wb.create_sheet(index = 0, title = "sheet 0")
#checking the sheet names
wb.sheetnames['sheet 0', 'Sheet', 'sheet 2']
#deleting a sheet
del wb['sheet 0']
#checking sheetnames
wb.sheetnames['Sheet', 'sheet 2']
#checking the sheet value
ws['B2'].value
null
#adding value to cell
ws['B2'] = 367
#checking value
ws['B2'].value
367
We often require formulas to be included in our Excel datasheet. We can easily add formulas using the Openpyxl module just like you add values to a cell.
For example:
import openpyxl
from openpyxl
import Workbook
wb = openpyxl.load_workbook("new1.xlsx")
ws = wb['Sheet']
ws['A9'] = '=SUM(A2:A8)'
wb.save("new2.xlsx")
The above program will add the formula (=SUM(A2:A8)) in cell A9. The result will be as below.
Two or more cells can be merged to a rectangular area using the method merge_cells(), and similarly, they can be unmerged using the method unmerge_cells().
For example:
Merge cells
#merge cells B2 to C9
ws.merge_cells('B2:C9')
ws['B2'] = "Merged cells"
Adding the above code to the previous example will merge cells as below.
#unmerge cells B2 to C9
ws.unmerge_cells('B2:C9')
The above code will unmerge cells from B2 to C9.
To insert an image we import the image function from the module openpyxl.drawing.image. We then load our image and add it to the cell as shown in the below example.
Example:
import openpyxl
from openpyxl
import Workbook
from openpyxl.drawing.image
import Image
wb = openpyxl.load_workbook("new1.xlsx")
ws = wb['Sheet']
#loading the image(should be in same folder)
img = Image('logo.png')
ws['A1'] = "Adding image"
#adjusting size
img.height = 130
img.width = 200
#adding img to cell A3
ws.add_image(img, 'A3')
wb.save("new2.xlsx")
Result:
Charts are essential to show a visualization of data. We can create charts from Excel data using the Openpyxl module chart. Different forms of charts such as line charts, bar charts, 3D line charts, etc., can be created. We need to create a reference that contains the data to be used for the chart, which is nothing but a selection of cells (rows and columns). I am using sample data to create a 3D bar chart in the below example:
Example
import openpyxl
from openpyxl
import Workbook
from openpyxl.chart
import BarChart3D, Reference, series
wb = openpyxl.load_workbook("example.xlsx")
ws = wb.active
values = Reference(ws, min_col = 3, min_row = 2, max_col = 3, max_row = 40)
chart = BarChart3D()
chart.add_data(values)
ws.add_chart(chart, "E3")
wb.save("MyChart.xlsx")
Result
Welcome to another video! In this video, We will cover how we can use python to automate Excel. I'll be going over everything from creating workbooks to accessing individual cells and stylizing cells. There is a ton of things that you can do with Excel but I'll just be covering the core/base things in OpenPyXl.
⭐️ Timestamps ⭐️
00:00 | Introduction
02:14 | Installing openpyxl
03:19 | Testing Installation
04:25 | Loading an Existing Workbook
06:46 | Accessing Worksheets
07:37 | Accessing Cell Values
08:58 | Saving Workbooks
09:52 | Creating, Listing and Changing Sheets
11:50 | Creating a New Workbook
12:39 | Adding/Appending Rows
14:26 | Accessing Multiple Cells
20:46 | Merging Cells
22:27 | Inserting and Deleting Rows
23:35 | Inserting and Deleting Columns
24:48 | Copying and Moving Cells
26:06 | Practical Example, Formulas & Cell Styling
📄 Resources 📄
OpenPyXL Docs: https://openpyxl.readthedocs.io/en/stable/
Code Written in This Tutorial: https://github.com/techwithtim/ExcelPythonTutorial
Subscribe: https://www.youtube.com/c/TechWithTim/featured