Harvest Reviews

1. CliffJones

   3 months ago
   Handy helper app

   Harvest has significantly improved our workflow. Its reporting make project management a breeze.

2. Elle Bennett

   | Webmaster at UK Landlord Tax | almost 2 years ago
   Excellent for tracking hours

   A nice simple interface and plenty of rich features really make this application essential.

   🏁 Competitors: Pomodone
3. stevezapalac

   almost 2 years ago
   One of the best Time Tracking App I have ever used.

   Has a lot of features when compared to it's competitors out there.

NumPy Reviews

Harvest mentions (14)

• software for planning upcoming months work

  If that’s not enough, I’ve had good experience with http://getharvest.com (and accompanying tools from them). Source: about 1 year ago

• Software Developer Mac Apps

  Https://getharvest.com/ : time tracker for contract work. Source: about 1 year ago

• What do you guys for invoicing outside Upwork?

  I use getharvest.com to track hourly and convert them to invoice. The only thing I don't like is that I have to add the task in the web dashboard rather than entering directly in the desktop app. There is 'note' field, but it won't show up in the invoice detail, so it is useless for me. Source: about 1 year ago

• Need help learning, can anyone suggest search terms so I can wrap my head around what I would like to do? Thanks

  I think for your business the best way to go is with a premade app for time logs and invoicing. My wife uses Harvest for her business: https://getharvest.com. Source: about 1 year ago

• New to graphic freelancing, how to take payments/send invoice?

  I use Harvestto invoice and track time. You can also use QuickBooks. Source: about 1 year ago

NumPy mentions (107)

• Element-wise vs Matrix vs Dot multiplication

  In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 3 months ago

• JSON in data science projects: tips & tricks

  Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 3 months ago

• Introducing Flama for Robust Machine Learning APIs

  Numpy: A library for scientific computing in Python. - Source: dev.to / 6 months ago

• A Comprehensive Guide to NumPy Arrays

  Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago

• Beginning Python: Project Management With PDM

  A majority of software in the modern world is built upon various third party packages. These packages help offload work that would otherwise be rather tedious. This includes interacting with cloud APIs, developing scientific applications, or even creating web applications. As you gain experience in python you'll be using more and more of these packages developed by others to power your own code. In this example... - Source: dev.to / 8 months ago