versus | Benchmark multiple API endpoints | Testing library

" It sounds as if rebasing "replays" commits, one after another (so sequentially) from the source branch over the changes in my working branch, is this the case? "

Yes.

" Furthermore, it does so, one develop commit at a time, until all the changes have been "replayed" into my feature branch, yes? "

No, it's the contrary. If you rebase your branch on origin/develop, all your branch's commits are to be replayed on top of origin/develop, not the other way around.

Finally, the difference between merge and rebase scenarios has been described in details everywhere, including on this site, but very broadly the merge workflow will add a merge commit to history. For that last part, take a look here for a start.

You must look at your usage profile. Do the request come constantly at a steady rate? Or are they spread out?

With a virtual machine you pay for the time it is running, it is not dependent on what it is doing.

With an Azure function consumption plan you pay per request. So when there are no requests there is no charge.

https://azure.microsoft.com/en-us/pricing/details/functions/ (Your 18 USD comes from this page?)

When a function has 500 MB to use, your code can use all the memory. When a VM has 500 MB of RAM a significant portion is used by the operating system.

Edit: As Ken mentioned in the comment with a VM you need to look after the server, so you also need to take that cost into consideration.

The compute capacity is the same given a steady constant continuous use where you turn off the VM when the 3M calls are finished. But the VM has additional costs that also need to be taken into consideration.

Note when you turn the VM off you still pay for the storage of the disks.

It looks like you're modeling the one-to-many relationship between Games and Results using a complex attribute (e.g. a list or objects) on the Game item. This is a completely valid approach to modeling one-to-many relationships and is best used when 1) the results data doesn't change (or change often) and 2) you don't have any access patterns around Results.

Since it sounds like you do have access patterns around Results, you'd be better off storing your Results in their own items.

For example, you might consider modeling results in the user partition with a PK=USER#user_id SK=RESULT#game_id. This would allow you to fetch results by User ID (QUERY where PK=USER#user_id SK begins_with RESULT). Alternatively, you could model results with a PK=RESULT#game_id SK=USER#user_id and create a GSI that swaps the PK/SK's which will allow you to group results by User.

I don't know the specifics around your access patterns, but can say that you'll need to move results into their own items if you want to support access patterns around game results.

Going with the WCU calculation guide here it looks like BatchWriteItem and PutItem both follows the same rounding off calculation for the size and will have same WCU consumed.

For PutItem, UpdateItem, and DeleteItem operations, DynamoDB rounds the item size up to the next 1 KB. For example, if you put or delete an item of 1.6 KB, DynamoDB rounds the item size up to 2 KB.

BatchWriteItem—Writes up to 25 items to one or more tables. DynamoDB processes each item in the batch as an individual PutItem or DeleteItem request (updates are not supported). So DynamoDB first rounds up the size of each item to the next 1 KB boundary, and then calculates the total size. The result is not necessarily the same as the total size of all the items. For example, if BatchWriteItem writes a 500-byte item and a 3.5 KB item, DynamoDB calculates the size as 5 KB (1 KB + 4 KB), not 4 KB (500 bytes + 3.5 KB).

Raster or bitmap fonts are represented in a number of different ways and there are bitmap font file standards that have been developed for both Linux and Windows. However raw data representation of bitmap fonts in programming language source code seems to vary depending on:

• the memory architecture of the target computer,
• the architecture and communication pathways to the display controller,
• character glyph height and width in pixels and
• the amount of memory for bitmap storage and what measures are taken to make that as small as possible.

A brief overview of bitmap fonts

A generic bitmap is a block of data in which individual bits are used to indicate a state of either on or off. One use of a bitmap is to store image data. Character glyphs can be created and stored as a collection of images, one for each character in the character set, so using a bitmap to encode and store each character image is a natural fit.

Bitmap fonts are bitmaps used to indicate how to display or print characters by turning on or off pixels or printing or not printing dots on a page. See Wikipedia Bitmap fonts

A bitmap font is one that stores each glyph as an array of pixels (that is, a bitmap). It is less commonly known as a raster font or a pixel font. Bitmap fonts are simply collections of raster images of glyphs. For each variant of the font, there is a complete set of glyph images, with each set containing an image for each character. For example, if a font has three sizes, and any combination of bold and italic, then there must be 12 complete sets of images.

A brief history of using bitmap fonts

The earliest user interface terminals such as teletype terminals used dot matrix printer mechanisms to print on rolls of paper. With the development of Cathode Ray Tube terminals bitmap fonts were readily transferable to that technology as dots of luminescence turned on and off by a scanning electron gun.

Earliest bitmap fonts were of a fixed height and width with the bitmap acting as a kind of stamp or pattern to print characters on the output medium, paper or display tube, with a fixed line height and a fixed line width such as the 80 columns and 24 lines of the DEC VT-100 terminal.

With increasing processing power, a more sophisticated typographical approach became available with vector fonts used to improve displayed text quality and provide improved scaling while also reducing memory required to describe the character glyphs.

In addition, while a matrix of dots or pixels worked fairly well for languages such as English, written languages with complex glyph forms were poorly served by bitmap fonts.

Representation of bitmap fonts in source code

There are a number of bitmap font file formats which provide a way to represent a bitmap font in a device independent description. For an example see Wikipedia topic - Glyph Bitmap Distribution Format

The Glyph Bitmap Distribution Format (BDF) by Adobe is a file format for storing bitmap fonts. The content takes the form of a text file intended to be human- and computer-readable. BDF is typically used in Unix X Window environments. It has largely been replaced by the PCF font format which is somewhat more efficient, and by scalable fonts such as OpenType and TrueType fonts.

Other bitmap standards such as XBM, Wikipedia topic - X BitMap, or XPM, Wikipedia topic - X PixMap, are source code components that describe bitmaps however many of these are not meant for bitmap fonts specifically but rather other graphical images such as icons, cursors, etc.

As bitmap fonts are an older format many times bitmap fonts are wrapped within another font standard such as TrueType in order to be compatible with the standard font subsystems of modern operating systems such as Linux and Windows.

However embedded systems that are running on the bare metal or using an RTOS will normally need the raw bitmap character image data in the form similar to the XBM format. See Encyclopedia of Graphics File Formats which has this example:

Following is an example of a 16x16 bitmap stored using both its X10 and X11 variations. Note that each array contains exactly the same data, but is stored using different data word types:

• have synthesized data that is similar to your dataframe
• plotting is simple, just need to select Client Total from index using .loc[]

I had this problem today and did npm install eslint-config-react-app like on github is recommended. After that console adviced me to install @babel/core and typescript, so i installed them by npm install @babel/core and npm install typescript

Your approach is close to solution but the syntax need a little bit changed to avoid the warning.

You can use .loc with the boolean index for filtering as the first parameter and the column name as second parameter , as follows:

Updating an object property in an array best practice is through map versus foreach. Every example as per the redux breaks out map into two functions 1. Update object properties/s and return object. Even on medium and other expert content it follows this format

This is generally true only if you really need a separate array. Your current logic is mutating the existing objects, and returning a shallow copy of the array. This is quite an odd thing to do, and is probably the source of why some may be frowning on your existing approach. Usually, you'd want to create a whole new array with new objects, instead of mutating the existing array - use rest syntax instead of Object.assign to keep things more concise: