1677892020
A comparison of data manipulation prowess using synthetic data and the GE Flight Quest data
Set up instructions
# Pkg.add("DataBench")
Synthetic benchmarks
Adapted from data.tables' official benchmarks
"Real-life" benchmarks
Uses GE Flight Quest data, the largest tabular dataset on Kaggle at the time of writing
Companion post
Speed of data manipulations in Julia vs R
Similar repos
https://github.com/szilard/benchm-databases
Author: xiaodaigh
Source Code: https://github.com/xiaodaigh/DataBench.jl
License: MIT, Unknown licenses found
1649209980
A cross-platform command line REPL for the rapid experimentation and exploration of C#. It supports intellisense, installing NuGet packages, and referencing local .NET projects and assemblies.
(click to view animation)
C# REPL provides the following features:
C# REPL is a .NET 6 global tool, and runs on Windows 10, Mac OS, and Linux. It can be installed via:
dotnet tool install -g csharprepl
If you're running on Mac OS Catalina (10.15) or later, make sure you follow any additional directions printed to the screen. You may need to update your PATH variable in order to use .NET global tools.
After installation is complete, run csharprepl
to begin. C# REPL can be updated via dotnet tool update -g csharprepl
.
Run csharprepl
from the command line to begin an interactive session. The default colorscheme uses the color palette defined by your terminal, but these colors can be changed using a theme.json
file provided as a command line argument.
Type some C# into the prompt and press Enter to run it. The result, if any, will be printed:
> Console.WriteLine("Hello World")
Hello World
> DateTime.Now.AddDays(8)
[6/7/2021 5:13:00 PM]
To evaluate multiple lines of code, use Shift+Enter to insert a newline:
> var x = 5;
var y = 8;
x * y
40
Additionally, if the statement is not a "complete statement" a newline will automatically be inserted when Enter is pressed. For example, in the below code, the first line is not a syntactically complete statement, so when we press enter we'll go down to a new line:
> if (x == 5)
| // caret position, after we press Enter on Line 1
Finally, pressing Ctrl+Enter will show a "detailed view" of the result. For example, for the DateTime.Now
expression below, on the first line we pressed Enter, and on the second line we pressed Ctrl+Enter to view more detailed output:
> DateTime.Now // Pressing Enter shows a reasonable representation
[5/30/2021 5:13:00 PM]
> DateTime.Now // Pressing Ctrl+Enter shows a detailed representation
[5/30/2021 5:13:00 PM] {
Date: [5/30/2021 12:00:00 AM],
Day: 30,
DayOfWeek: Sunday,
DayOfYear: 150,
Hour: 17,
InternalKind: 9223372036854775808,
InternalTicks: 637579915804530992,
Kind: Local,
Millisecond: 453,
Minute: 13,
Month: 5,
Second: 0,
Ticks: 637579915804530992,
TimeOfDay: [17:13:00.4530992],
Year: 2021,
_dateData: 9860951952659306800
}
A note on semicolons: C# expressions do not require semicolons, but statements do. If a statement is missing a required semicolon, a newline will be added instead of trying to run the syntatically incomplete statement; simply type the semicolon to complete the statement.
> var now = DateTime.Now; // assignment statement, semicolon required
> DateTime.Now.AddDays(8) // expression, we don't need a semicolon
[6/7/2021 5:03:05 PM]
Use the #r
command to add assembly or nuget references.
#r "AssemblyName"
or #r "path/to/assembly.dll"
#r "path/to/project.csproj"
. Solution files (.sln) can also be referenced.#r "nuget: PackageName"
to install the latest version of a package, or #r "nuget: PackageName, 13.0.5"
to install a specific version (13.0.5 in this case).To run ASP.NET applications inside the REPL, start the csharprepl
application with the --framework
parameter, specifying the Microsoft.AspNetCore.App
shared framework. Then, use the above #r
command to reference the application DLL. See the Command Line Configuration section below for more details.
csharprepl --framework Microsoft.AspNetCore.App
The C# REPL supports multiple configuration flags to control startup, behavior, and appearance:
csharprepl [OPTIONS] [response-file.rsp] [script-file.csx] [-- <additional-arguments>]
Supported options are:
-r <dll>
or --reference <dll>
: Reference an assembly, project file, or nuget package. Can be specified multiple times. Uses the same syntax as #r
statements inside the REPL. For example, csharprepl -r "nuget:Newtonsoft.Json" "path/to/myproj.csproj"
-u <namespace>
or --using <namespace>
: Add a using statement. Can be specified multiple times.-f <framework>
or --framework <framework>
: Reference a shared framework. The available shared frameworks depends on the local .NET installation, and can be useful when running an ASP.NET application from the REPL. Example frameworks are:-t <theme.json>
or --theme <theme.json>
: Read a theme file for syntax highlighting. This theme file associates C# syntax classifications with colors. The color values can be full RGB, or ANSI color names (defined in your terminal's theme). The NO_COLOR standard is supported.--trace
: Produce a trace file in the current directory that logs CSharpRepl internals. Useful for CSharpRepl bug reports.-v
or --version
: Show version number and exit.-h
or --help
: Show help and exit.response-file.rsp
: A filepath of an .rsp file, containing any of the above command line options.script-file.csx
: A filepath of a .csx file, containing lines of C# to evaluate before starting the REPL. Arguments to this script can be passed as <additional-arguments>
, after a double hyphen (--
), and will be available in a global args
variable.If you have dotnet-suggest
enabled, all options can be tab-completed, including values provided to --framework
and .NET namespaces provided to --using
.
C# REPL is a standalone software application, but it can be useful to integrate it with other developer tools:
To add C# REPL as a menu entry in Windows Terminal, add the following profile to Windows Terminal's settings.json
configuration file (under the JSON property profiles.list
):
{
"name": "C# REPL",
"commandline": "csharprepl"
},
To get the exact colors shown in the screenshots in this README, install the Windows Terminal Dracula theme.
To use the C# REPL with Visual Studio Code, simply run the csharprepl
command in the Visual Studio Code terminal. To send commands to the REPL, use the built-in Terminal: Run Selected Text In Active Terminal
command from the Command Palette (workbench.action.terminal.runSelectedText
).
To add the C# REPL to the Windows Start Menu for quick access, you can run the following PowerShell command, which will start C# REPL in Windows Terminal:
$shell = New-Object -ComObject WScript.Shell
$shortcut = $shell.CreateShortcut("$env:appdata\Microsoft\Windows\Start Menu\Programs\csharprepl.lnk")
$shortcut.TargetPath = "wt.exe"
$shortcut.Arguments = "-w 0 nt csharprepl.exe"
$shortcut.Save()
You may also wish to add a shorter alias for C# REPL, which can be done by creating a .cmd
file somewhere on your path. For example, put the following contents in C:\Users\username\.dotnet\tools\csr.cmd
:
wt -w 0 nt csharprepl
This will allow you to launch C# REPL by running csr
from anywhere that accepts Windows commands, like the Window Run dialog.
This project is far from being the first REPL for C#. Here are some other projects; if this project doesn't suit you, another one might!
Visual Studio's C# Interactive pane is full-featured (it has syntax highlighting and intellisense) and is part of Visual Studio. This deep integration with Visual Studio is both a benefit from a workflow perspective, and a drawback as it's not cross-platform. As far as I know, the C# Interactive pane does not support NuGet packages or navigating to documentation/source code. Subjectively, it does not follow typical command line keybindings, so can feel a bit foreign.
csi.exe ships with C# and is a command line REPL. It's great because it's a cross platform REPL that comes out of the box, but it doesn't support syntax highlighting or autocompletion.
dotnet script allows you to run C# scripts from the command line. It has a REPL built-in, but the predominant focus seems to be as a script runner. It's a great tool, though, and has a strong community following.
dotnet interactive is a tool from Microsoft that creates a Jupyter notebook for C#, runnable through Visual Studio Code. It also provides a general framework useful for running REPLs.
Download Details:
Author: waf
Source Code: https://github.com/waf/CSharpRepl
License: MPL-2.0 License
1620466520
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition
1677892020
A comparison of data manipulation prowess using synthetic data and the GE Flight Quest data
Set up instructions
# Pkg.add("DataBench")
Synthetic benchmarks
Adapted from data.tables' official benchmarks
"Real-life" benchmarks
Uses GE Flight Quest data, the largest tabular dataset on Kaggle at the time of writing
Companion post
Speed of data manipulations in Julia vs R
Similar repos
https://github.com/szilard/benchm-databases
Author: xiaodaigh
Source Code: https://github.com/xiaodaigh/DataBench.jl
License: MIT, Unknown licenses found
1623945720
What are the average house prices in different cities of the US? What are the total sales amounts of different product groups in a store? What are the average salaries in different companies?
All these questions can be answered by using a grouping operation given that we have proper data. Most data analysis libraries and frameworks implement a function to perform such operations.
In this article, we will compare two of the most popular data analysis libraries with regards to tasks that involve grouping. The first one is Python Pandas and the other is R data table.
We will be using the Melbourne housing dataset available on Kaggle for the examples. We first import the libraries and read the dataset.
## pandas
import pandas as pd
melb = pd.read_csv("/content/melb_data.csv")
## data.table
library(data.table)
melb <- fread("datasets/melb_data.csv")
#python #data-science #r #how grouping works with python pandas vs r data table #grouping works #data table
1620629020
The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management