Trending February 2024 # Three Useful Creative Writing Applications For Linux Users # Suggested March 2024 # Top 11 Popular

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If you are a writer, you would have used tools like Final Draft or Scrivener to create your work. What if you are a Linux user and those tools are not available on Linux platform? What choices do you have to create your novels, scripts, or screenplays. Well, you are not totally lost. Here are some Linux-based creative writing applications for you.

1. Celtx

One of the main features of Celtx includes index cards you can use to brainstorm and organize your thoughts by plotline, the ability to arrange scenes into chapters and parts. There are two versions of the application available: a free version, and a premium version that provides extra features such as the ability to arrange index cards into plot and timeline views (they are displayed in a flat list only in the free version).

2. Plume

In contrast, Plume Creator is focused on prose-based creative writing. It also maintains your writing in scenes and chapters (with early support for an outliner), but in addition to characters also helps manage places and items, which are key features for writers of fiction. Plume lets you maintain a collection of these elements and associate them with your work(s) as appropriate for easy reference in the right-hand panel.

Plume also features a fullscreen (i.e. distraction-free) interface, and the ability to attach a synopsis and notes individually to the novel as a whole, or at the chapter or scene level. It is available for download as a .deb file.

3. Storybook

Don’t let tools like the Final Draft and Scrivener fool you… Mac and Windows aren’t the only creative writing platform in town (although Scrivener has been testing a Linux beta for some time now). If you’re a Linux user with an idea for a novel, you’ve got access to all the tools you need.

Let us know if you are using other writing tools not mentioned in the above list.

Image credit: write

Aaron Peters

Aaron is an interactive business analyst, information architect, and project manager who has been using Linux since the days of Caldera. A KDE and Android fanboy, he’ll sit down and install anything at any time, just to see if he can make it work. He has a special interest in integration of Linux desktops with other systems, such as Android, small business applications and webapps, and even paper.

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Dropbox Alternatives For Linux Users

Like many of you, I too have found myself wooed by the convenience of using Dropbox. It’s cross platform, simple to setup and provides a cloud storage option for those who might otherwise be less inclined to store files off-site. In this article I’ll explore alternatives to Dropbox for Linux users.

When BitTorrent Sync first became popular, I loved it. I found it was faster than competing technologies and I could sync huge files on my LAN very quickly. I loved the fact that syncing to a third party service (a cloud) was never part of the equation. WAN syncing also works well, for those needing to sync over the Internet.

What I liked: BitTorrent Sync is simple to use, doesn’t sync to the “cloud” and has no folder size limits. The UpnP port mapping worked flawlessly with my router.

What I didn’t like: BitTorrent Sync doesn’t offer selective sync with their free version. It also doesn’t allow me to change my folder access permissions. Not having the ability to sync to the “cloud” also means any backup of your files is on you. The strong encryption is also nice, although we’re talking about a proprietary application.

Summary: If you’re a heavy Dropbox user and are willing to pay the one time fee, you could save yourself some cash overall.

Sync your files between computers over your LAN or across the web, using strong encryption and open source software. When BitTorrent Sync first mentioned their new premium version some users felt betrayed; they felt it should have remained completely free. Instead, the free version lost features to the paid version. For some, switching to Syncthing was the natural course of action.

What I liked: Syncthing is open source, has packages for every sort of platform you can imagine and is relatively easy to setup…usually. I also love the ssh support in case you’re needing to avoid the web UI when away from home.

What I didn’t like: Despite Syncthing providing options for UpnP, I’ve never had much success with it. I’ve read that this could be the result of a timeout issue or perhaps the router doesn’t know what to do with the discovery service. I did eventually have it working with UpnP after changing out the router with another one. So be aware, UpnP can be hit and miss.

Summary: If you’re able to iron out or avoid the issues with UpnP, Syncthing is a very strong contender to replace Dropbox. Like BitTorrent Sync, there is no cloud storage in the equation.

I decided to include SpiderOak with these Dropbox alternatives as it provides device syncing in addition to data backup. Most people use SpiderOak as a secure means of backing up their files. I’ve found it’s also useful for syncing between PCs running SpiderOak.

What I liked: SpiderOak provides a zero-knowledge storage platform. This means your privacy is fully respected as your data is encrpted at all times except when you decrypt it on your own PC. I’ve also found that their storage (like Dropbox) is cheap. You can get upto 1 TB of data storage for $12 USD per month.

What I didn’t like: SpiderOak uses some open source components. Unfortunately, there are still some aspects of SpiderOak that are not fully open source. The software for Linux feels a bit bloated. Great UI, but the flow of the application can bring an older computer to a screeching halt.

Summary: If you want end to end encryption with better privacy options than Dropbox, then SpiderOak is for you. This is also a great option if you’re needing to backup your files in addition to simply syncing them.

The next option is a bit of a rough spot with many Linux users. Despite years of empty promises, Google has yet to deliver on a working Google Drive client for Linux. Thankfully this is not a big deal– there are alternatives. Both the latest Gnome desktop and Insync provide great Google Drive access for Linux users.

What I liked: Google Drive offers free storage up to 15 GB. An additional 100 GB is only $1.99 USD. Syncing is easy, simply run one Insync or Gnome desktop to keep your files accessible. Most people waiting on Gnome to make this happen will end up using alternatives like Insync in the meantime.

What I didn’t like: Cost aside, the lack of commitment from Google to Linux users in this space is frustrating. Bundle this with the fact that Google is famous for completely dumping products makes me hesitant to rely on Google Drive for anything terribly important.

Unlike the other options listed here, Tarsnap puts Linux first. Going even deeper, Tarsnap doesn’t support Windows. The rates are very reasonable, as it uses AWS for its storage. Setting aside its geeky nature, Tarsnap is a big hit among a number of Linux users.

What I liked: Cost. Tarsnap is setup to provide reliable backup at a fair cost. If you set it up to do so, Tarsnap can be used to sync files between machines. Tarsnap also provides excellent security and is open source software.

What I didn’t like: It’s pretty difficult to use for a casual Linux user. If you’re comfortable reading documentation and using the command line however, this is a great fit.

Summary: If you are dead set against using more mainstream options or simply would prefer to stick to using the command line, then Tarsnap is a fantastic option.

Unlike the other Dropbox alternatives listed here, ownCloud is more of a Google Apps replacement. Collaborate document editing, calendars, galleries and more – ownCloud is a full software suite designed to run on your own server. Like Google Drive, you can also use ownCloud to sync files between machines.

What I liked: Once installed, ownCloud is dead simple to use and provides a great open source experience. It feels a lot like Google Apps. You can share your files with anyone you wish and ownCloud offers you decent encryption and security.

What I didn’t like: You need to install the software on your own hardware to act as a server. Not a big deal to geeks, but it could be confusing for a casual user expecting a Syncthing like experience. In the past, I’ve had ownCloud choke a bit on larger files. Though I’ve heard this has been resolved but I’d urge caution until you feel comfortable with it handling your most important files.

Let’s face it, there are a ton of solutions out there. And there may even be some options available I’ve never heard of. Using the Comments form below, share your favorite Dropbox alternatives. How do you use them and do you rely on cloud based storage or direction solutions like Syncthing. Hit the Comments, share your ideas and experiences in this arena.

Photo courtesy of Shutterstock.

Steam Is No Longer Just For Windows, Mac, And Linux Users

Steam is no longer just for Windows, Mac, and Linux users

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We all know Steam as our go-to PC gaming platform and store.

Now, Ellon Musk is trying to integrate Steam into Tesla vehicles.

The Tesla CEO actually promised support for the Steam titles.

Most of us have used Steam at least once, and the platform is undoubtedly the most popular online gaming platform/store in the world.

As you know, Steam is available to all Windows, Mac, or Linux users for free. The only thing you pay for when you use Steam is the games themselves.

In fact, Steam has become so popular over the years that it’s pretty much impossible to mention PC gaming without at least saying the app’s name at least once.

And, since you use Steam on the Windows OS, we can show you what to do if an update is stuck or not downloading, or how to add Microsoft Store and Xbox Games on Steam.

The company has always made efforts to collaborate with the Redmond tech giant, even providing Windows drivers for its latest Steam Deck device.

By the way, if you ordered yourself a Steam Deck handheld gaming PC, here’s a calculator to help you anticipate when your device will ship.

Why did we say that the app will no longer be only for Windows, Mac, and Linux users? Because, get this, it’s going to be an integral part of Tesla cars as well.

We’re making progress with Steam integration. Demo probably next month.

— Elon Musk (@elonmusk) July 15, 2023

You will be able to run Steam and play games in your Tesla

Some of you might think this is a joke, but Tesla is apparently looking to expand its collection of in-car games by integrating the Steam app. 

In fact, Tesla CEO Elon Musk personally said that the company’s making progress with Steam integration and that we can expect a demo probably next month (August 2023).

If you know only a little bit about these cars, you surely found out that Tesla already offers a number of games through the built-in Tesla Arcade.

That being said, you have to realize how big adding Steam’s digital storefront to the car’s software could actually be.

Such a move could give users access to the entire Steam gaming catalog, which means that you can take a break from your drive, pull over, have a sandwich, and play Cyberpunk 2077.

Keep in mind that, even though this information is out, it’s still unknown if the integration will go so far as to allow users to make purchases on Steam while sitting in their cars.

team

Another question is if the car’s software can support all games in the Steam catalog and if this will affect the car’s performance at all.

People that kept a close eye on this matter remember that Ellon Musk still hasn’t delivered on promises to bring Cyberpunk 2077 and The Witcher to newer Model S and X vehicles.

Before you ask how can these cars run such complex and demanding games, know that they come outfitted with an AMD Ryzezn processor and a discrete AMD RDNA 2 GPU.

So, it’s safe to say that we can imagine our Tesla vehicles as extensions of our gaming dens, provided we don’t bring other devices on our trips.

Things are moving so fast technology-wise, that it would be surprising to see Windows 11, or even the upcoming Windows 12 running in these vehicles.

We remind you that recent details point to Microsoft moving back to a three-year release for new Windows operating systems.

This means that newer versions of Windows could end up being the official OS for quite a number of cars, provided Microsoft creates new partnerships in that direction.

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How To Install Adobe Creative Cloud Apps In Linux

Adobe’s suite of Creative Cloud apps are relied upon by many people for professional and personal use, but these programs have not been ported to Linux officially despite incessant requests from Linux users. This is presumably because of the tiny market share that Desktop Linux currently has.

Despite this, the community has found ways to bring Adobe apps to your Linux Desktop through Wine. But it can be difficult to get the Creative Cloud suite working in Wine due to compatibility issues with the multiple versions of the setup program available from Adobe’s website.

To solve this problem, Corbin Davenport created an installation script that helps you install any of the Adobe Creative Cloud apps on Linux without all the hassle. The script takes care of all the necessary configuration details and makes use of a lot of patches and tweaks to get things working.

Installing PlayOnLinux

The Creative Cloud Script was made to work with PlayOnLinux which is a GUI Front-End for Wine that allows you to easily install and use numerous apps and games designed to run with Microsoft Windows, so you need to install that first. Here’s how to install PlayOnLinux on the following Linux Distributions:

Ubuntu and Ubuntu-based distributions

sudo

apt

install

playonlinux

Debian

sudo

apt-get install

playonlinux

Fedora

sudo

dnf

install

playonlinux

OpenSUSE

sudo

zypper

install

playonlinux

Arch Linux

sudo

pacman

-S

playonlinux Other Linux Distributions

Even if your distribution does not have PlayOnLinux in its repositories, there’s still a good chance you’ll be able to install it through some other means. There’s a generic package provided on the PlayOnLinux website that should work with any Linux distro, so consider checking that first.

How to Use the Creative Cloud Script

Once you have PlayOnLinux installed, download the Creative Cloud script from its Github Repository and save it to your computer.

Hit “Next” to begin the installation process. This could take a while, so be patient. Eventually, once the installation completes, you should be able to launch Adobe Application Manager from PlayOnLinux and use it to sign in with your Adobe ID and download your Creative Cloud applications.

Note that this script does not give you free access to Adobe’s Creative suite. It only makes it easy for you to set up the Adobe Creative Cloud desktop program which can be used to install and update Photoshop, Lightroom, Dreamweaver, Illustrator, and other apps.

You will need a free Adobe ID and a paid subscription to download and use most of the applications in the suite.

Wrap Up

This script is not required to run Adobe CC apps on Linux. With a little patience, you can reproduce the same results even without using PlayOnLinux. However, using this script will make things much easier for you.

Keep in mind that not every Adobe CC app will run on your Linux PC. According to the developer, only Photoshop CC, Bridge CC, Lightroom 5, and the Creative Cloud manager have been extensively tested, so your mileage may vary.

Ayo Isaiah is a freelance writer from Lagos who loves everything technology with a particular interest in open-source software. Follow him on Twitter.

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Airflow For Orchestrating Rest Api Applications

This article was published as a part of the Data Science Blogathon.

“Apache Airflow is the most widely-adopted, open-source workflow management platform for data engineering pipelines. It started at Airbnb in October 2014 as a solution to manage the company’s increasingly complex workflows. Most organizations today with complex data pipelines to be managed leverage Apache Airflow to schedule, sequence, monitor the workflows.”

Airflow provides an easy-to-use, intuitive workflow system where you can declaratively define the sequencing of tasks (also known as

DAG

or Directed Acyclic Graph). The Airflow workflow scheduler works out the magic and takes care of scheduling, triggering, and retrying the tasks in the correct order.  

“Start Task4 only after Task1, Task2, and Task3 have been completed….”

“Retry Task2 upto 3 times with an interval of 1 minute if it fails…”

“Which task took the longest in the workflow? …”

“What time did taskN take today vs one week back? …”

“Email the team when a critical task fails…”

The Use Case for Airflow

So, where does a workflow management system fit? And how do you know you need to use it? Let’s say you are working for the IT division of a health care organization, and you need to run some analytics on patient records that you receive from a vendor hospital. You have developed that awesome Apache Spark-based application, which is working like a charm. You need that application run daily against the data that comes in from the hospital. A further requirement is that the output of that analysis needs to be pushed as input to a time-critical downstream application which determines the composition and quantity of factory production units for a test medicine for that day.

Initially, a simple cron job or a Jenkins-based job might suffice until things get bigger. Let’s say two more upstream hospitals get added to the fray. One pushes data to an S3 bucket; another gives a REST API-based interface from which you need to fetch data, and yet another in-house system dumps data to a database. You need to now run your analytics application against the data from all these upstream systems before running the downstream app. This is where the beauty of Airflow comes into play.

Airflow as a mainstream DevOps tool has been widely adopted since it was launched eight years ago to orchestrate BigData and ETL pipelines. As your systems and processes become bigger, managing the scalability and monitoring using custom scripts or cron-based solutions becomes difficult—this is where it fits in.

Airflow UI

times the task started/ended.

The Tree View UI shows you the historical runs broken down by tasks – this is most useful when you want to compare performance between historical runs.

REST API with Python Operators

There are  several operators and provider packages that Apache Airflow supports. Depending on your use case, you get to pick and choose what is most suitable. When I started learning Airflow, what I found most helpful and flexible were the Python-based operators. My applications were running in less than 24 hours with the combination of PythonOperator and PythonSensor 

With these two, you should be able to fit in the general use case described above. All you need is basic Python knowledge!

Structure of an A G

1. First come the imports:

2. Then comes the definition of the DAG constructor/initialization.

Here’s where you give the name of the workflow process that you want to see in the UI, the default retries for tasks, etc

dag = DAG( 'patient_data_analysis', default_args={'retries': 1}, start_date=datetime(2024, 1, 1), catchup=False, ) dag.doc_md = __doc__ ## Operators start = DummyOperator(task_id='start', dag=dag) op1 = PythonOperator( task_id='watch_for_data_dump_on_s3_bucket_pushed_byx_upstream_application_1', python_callable= _placeholder_function1, dag=dag) op2 = PythonOperator( task_id='fetch_data_from_upstream_REST_application2_and_dump_to_s3', python_callable= _placeholder_function2, dag=dag) op3 = PythonOperator( task_id='fetch_data_from_upstream_cloudant_application3_and_dump_to_s3', python_callable= _placeholder_function3, dag=dag) op4 = PythonOperator( task_id='run_analysis_on_all_patient_data_on_s3_dumps', python_callable= _placeholder_function4, dag=dag) determine_production_dosage = BranchPythonOperator( task_id='determine_production_dosage', python_callable=_determine_production_dosage, dag=dag ) production_path_1 = PythonOperator( task_id='production_path_1', python_callable= _placeholder_function5, dag=dag) production_path_2 = PythonOperator( task_id='production_path_2', python_callable= _placeholder_function6, dag=dag) end = DummyOperator(task_id='end',trigger_rule='one_success', dag=dag)

Here is where we have the breakdown of tasks in the flow. We have used three kinds of Operators.

PythonOperator –  which calls the Python callable or function which contains the actual task processing logic

BranchPythonOperator  – which is useful when you want the workflow to take different paths based on some conditional logic.

DummyOperator – which is a convenience operator to try out some POC flow quickly or in this case- gives a structure to the flow  – start and end.

Note that all the operators are connected using the same “dag” object reference.

4. Sequence your tasks

## Flow

The dependencies between your tasks can be declared using this intuitive flow notation.

The start operator will kick off three tasks in parallel – op1, op2, op3

Only when op1, op2, and op3 are done the op4 task will get started

The determine_production_dosage can result in either of the paths production_path_1 or production_path_2

And finally, execution of either path results in the end.



In this case, I have just given placeholder functions. We’ll get into what it should hold in the next section.  Special mention to the _determine_production_dosage(). This is the function called by the branch operator. As the code illustrates, this function’s return value is the operator’s name in the workflow.

PythonOperator and PythonSensor Combo

The following working code covers the following concepts.

How to use the  PythonOperator and callable to make REST API calls to generate a Bearer Token

And use that Bearer Token in subsequent API calls that call some business logic (in this case, it is calling a Spark application on a cloud provider API)

Concept of passing data between tasks using xcom

How to use PythonSensor operator to poll/wait for asynchronous task completion

How to dynamically construct the REST API endpoint based on the value returned from a previous task ( NOTE: This is one use case where I found the power and simplicity of PythonOperator come into play. I had initially tried the SimpleHttpOperator – but found the PythonOperator to be more flexible! )

Source code for serverless_spark_pipeline.py

## Import statements and DAG definition

import json import requests from datetime import datetime from airflow import DAG from airflow.operators.python import PythonOperator from airflow.sensors.python import PythonSensor dag = DAG( 'serverless_spark_pipeline', default_args={'retries': 1}, start_date=datetime(2024, 1, 1), catchup=False, ) dag.doc_md = __doc__

## Python callable for getting a Bearer Token

api_key='CHANGEME' def _get_iam_token(ti): headers={"Authorization": "Basic Yng6Yng=", "Content-Type": "application/x-www-form-urlencoded"} data="grant_type=urn:ibm:params:oauth:grant-type:apikey&apikey="+api_key res = requests.post(url=iam_end_point,headers=headers,data=data) ## Push the token using key, value ti.xcom_push(key='access_token', value= access_token)

## Python Operator for getting the Bearer Token; It calls the Python callable _get_iam_token

generate_iam_token = PythonOperator( task_id = 'get_iam_token', python_callable= _get_iam_token, dag=dag)

## Python callable for calling a REST API

instance_id='CHANGEME' def _submit_spark_application(ti): # Pull the bearer token and use it to submit to REST API access_token=ti.xcom_pull(key='access_token') headers = {"Authorization": "Bearer " + access_token, "Content-type": "application/json"} finalurl = url+instance_id+'/spark_applications' data=json.dumps({"application_details": {"application": "/opt/ibm/spark/examples/src/main/python/wordcount.py", "arguments": ["/opt/ibm/spark/examples/src/main/resources/people.txt"]}}) res = requests.post(finalurl,headers=headers,data=data) # Push the application id - to be used on a downstream task ti.xcom_push(key='application_id', value= application_id)

## Python Operator for submitting the Spark Application; It calls the Python callable _submit_spark_application

submit_spark_application = PythonOperator( task_id = 'submit_spark_application', python_callable= _submit_spark_application, dag=dag) def _track_application(ti): # Pull the application id from an upstream task and use it.. application_id=ti.xcom_pull(key='application_id') access_token=ti.xcom_pull(key='access_token') headers = {'Authorization': 'Bearer ' + access_token} # Construct the REST API endpoint dynamically based on the data # from a previous API call finalurl = ae_url+instance_id+'/spark_applications/'+application_id+'/state' res = requests.get(finalurl,headers=headers) # Keep polling the REST API to check state of application submission until a # terminal state is reached if state == 'finished' or state == 'failed': # Push the value of state as xcom key, value pair. # It can be later used for example in a BranchPythonOperator t1.xcom_push(key='state',value=state) return True else: return False

## Python Sensor for tracking a REST APU. It calls the Python callable _track_application

  track_application = PythonSensor( task_id = 'track_application', python_callable= _track_application, dag=dag)

## Operator flow

This example is based on a REST API call to a cloud provider API that submits a spark application, gets the application ID, and keeps polling for the application’s state based on that application ID. And finally, when the application either finishes or fails, it ends the workflow execution.

The Python callable functions make use of the standard requests module. In the example above, POST and GET. You can use the same approach for other REST API calls, PATCH, PUT, DELETE, etc.

End Notes

Here’s a snapshot of the main DAG UI page. If you are starting Airflow, here are some newbie tips.

You need to toggle and enable the DAG to make it active and execute automatically through the tasks.

Also, be aware that whenever you make a change in the DAG file, it takes about 1 minute to refresh your code and reflect it in the DAG Code tab in the UI.  (The DAG files, which are nothing but python files, are located in the airflow/dags folder of your installation)

This article showed you how to get quickly started with

A simple working DAG that you can get it up and running by defining the sequencing of tasks

Introduction to Python-based operators and sensors that can be easily adapted to call any backend REST API services/applications

How to orchestrate various asynchronous REST API services by polling and passing the relevant data between tasks for further processing

Depending on the use case, your tasks’ data source and data sink. You will need to evaluate what Airflow operators are suitable. Many tuning knobs for airflow can be further configured as you get deeper

The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.

Related

5 Tips For Writing Your Self

4. Track your accomplishments

Providing hard data to show what you’ve done throughout the year is highly beneficial. Employees and managers may roughly understand how you have performed but having concrete numbers to back up any assertion strengthens the validity of your self-assessment.

“If employees … spend 10 seconds a day writing down their one biggest accomplishment, success, metric hit, feedback received for that day, they’d have 10 times more data than they’d ever need for self-assessment,” said Mike Mannon, president of WD Communications.

Hank Yuloff, the owner of Yuloff Creative Marketing Solutions, said continuous evaluation of your performance can make it much easier to ground your self-assessment in facts and measurable data.

“We teach our clients to keep a list of daily and weekly accomplishments so that when it is time for the self-assessment, there is very little guesswork as to how valuable they are to the company,” Yuloff said.

5. Be professional

You should always be professional when writing self-assessments. This means not bashing the boss for poor leadership or criticizing co-workers for making your life more difficult. It also means not gushing over a co-worker or manager you like. Whether you are providing critical or positive feedback, professionalism is important.

Being professional means giving the appraisal its due attention, like any other important project that crosses your desk. Dominique Jones, chief people officer at BusPatrol, recommends treating your self-evaluation like a work of art that builds over time. She said you’ll be much happier with the result if you give yourself time to reflect and carefully support your self-assessment.

“Use examples to support your assertions and … make sure that you spell- and grammar-check your documents,” Jones wrote in a blog post. “These are all signs of how seriously you take the process and its importance to you.”

Self evaluation example statements

Keeping things simple and using short, declarative bullet points are key to writing an effective self-assessment. While the exact nature of your self-assessment might depend on your industry or your job description, this basic model can help guide you in writing a self-evaluation.

Strengths

I am a dedicated employee who understands my role and responsibilities, as well as the larger mission of our business. I strive to both do my job and make this company successful.

I am a good communicator who stays on task and helps rally the team when cooperation is needed to meet a deadline or solve a problem.

I am a creative thinker who can develop novel solutions and improve conventional ways of doing things.

Weaknesses

I am somewhat disorganized, which often impacts my productivity. I have learned how to manage my time better and intentionally direct my efforts. While it remains a challenge, I have seen some progress and look forward to continually improving.

Sometimes, I do not ask for help when I could benefit from assistance. I am always willing to help my teammates, and I know they feel the same way, so I will try to be more vocal about when I need a helping hand moving forward.

Core values

I believe in teamwork and cooperation to overcome any obstacle.

I value respect and transparency between employees and managers.

I value friendship and building warm relationships within the workplace.

I strive to be a welcoming and helpful presence to my co-workers.

Accomplishments

I never missed a deadline in the past year and often submitted my work early.

I’ve gone beyond my job description to ensure our team operates optimally, staying late and helping others whenever it could contribute to our collective goal.

I created and delivered a presentation, stepping outside my comfort zone to do so. It was well received and bolstered my confidence regarding public speaking.

Goals

I want to continue developing my presentation and public speaking skills. As a weakness that I listed on previous self-assessments, it is gratifying to see that I have made some progress on this skill set, and I would like to double down on the growth.

I aspire to enter a managerial role. I enjoy working closely with my teammates and considering the bigger picture, and I often efficiently help direct resources. I could see myself as a manager who helps facilitate teamwork and encourages workers to do their best.

Feedback

My manager is pleasant and transparent, and they always set clear expectations. I never have to guess where I stand. I appreciate the openness and direct communication.

I want to be more involved in decision-making at the team level. I believe each team member has unique insights that supervisors cannot fully understand since their perspective is different. I believe involving staff members in strategic planning could greatly improve results.

Did You Know?

You should keep your self-assessment short and simple by using bullet points.

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