1661388540
A very simple package for accessing elements in the Periodic Table! š„
Since PeriodicTable is registered in Julia's General Registry, you can readily install it with
] add PeriodicTable
PeriodicTable.jl provides a Julia interface to a small database of element properties for all of the elements in the periodic table. In particular PeriodicTable
exports a global variable called elements
, which is a collection of Element
data structures.
julia> using PeriodicTable
julia> elements
Elements(ā¦119 elementsā¦):
H He
Li Be B C N O F Ne
Na Mg Al Si P S Cl Ar
K Ca Sc Ti V Cr Mn Fe Co Ni Cu Zn Ga Ge As Se Br Kr
Rb Sr Y Zr Nb Mo Tc Ru Rh Pd Ag Cd In Sn Sb Te I Xe
Cs Ba Hf Ta W Re Os Ir Pt Au Hg Tl Pb Bi Po At Rn
Fr Ra Rf Db Sg Bh Hs Mt Ds Rg Cn Nh Fl Mc Lv Ts Og
Uue
La Ce Pr Nd Pm Sm Eu Gd Tb Dy Ho Er Tm Yb Lu
Ac Th Pa U Np Pu Am Cm Bk Cf Es Fm Md No Lr
You can look up elements by name (case-insensitive) via elements["oxygen"]
, by symbol via elements[:O]
, or by number via elements[8]
, for example.
Each element has fields name
, appearance
, atomic_mass
, boil
, category
, color
, density
, discovered_by
, melt
, molar_heat
, named_by
, number
, period
, phase
, source
, spectral_img
, summary
, symbol
, xpos
, ypos
, shells
.
All physical quantities are unitful.
The data is pretty-printed when you look up an element in the Julia REPL. For example:
julia> elements["oxygen"]
Oxygen (O), number 8:
category: diatomic nonmetal
atomic mass: 15.999 u
density: 1.429 g/cm³
melting point: 54.36 K
boiling point: 90.188 K
phase: Gas
shells: [2, 6]
eā»-configuration: 1s² 2s² 2pā“
summary: Oxygen is a chemical element with symbol O and atomic number 8. It is a member of the chalcogen group on the periodic table and is a highly reactive nonmetal and oxidizing agent that readily forms compounds (notably oxides) with most elements. By mass, oxygen is the third-most abundant element in the universe, after hydrogen and helium.
discovered by: Carl Wilhelm Scheele
named by: Antoine Lavoisier
source: https://en.wikipedia.org/wiki/Oxygen
spectral image: https://en.wikipedia.org/wiki/File:Oxygen_spectre.jpg
Alternatively, you may want to get a list of elements,
julia> elements[1:4]
4-element Array{PeriodicTable.Element,1}:
Element(Hydrogen)
Element(Helium)
Element(Lithium)
Element(Beryllium)
A nice interactive visualization of the periodic table, based on PeriodicTable.jl, can be found here.
The data used for this package has been pulled up in parts from here. Some information has been (and will be) added over time.
Author: JuliaPhysics
Source Code: https://github.com/JuliaPhysics/PeriodicTable.jl
License: View license
1620228780
DevOps is a widely heard term in todayās market as the majority of the enterprises have opted to use the DevOps tools. Still many enterprises require a presentation for understanding the developments involved with using the DevOps tools. DevOps include social advancement which is a breakdown of the dividers and the storehouses between programming and activities with the tools and new techniques that empower these changes.
DevOps tools have speeded up the change in programming makers put up their applications and advance the applications for further sale to the public. The primary motivation for using DevOps tools as said by the majority of users is its quick development.
The Periodic Table of DevOps Tools is considered to be a dynamic, implant capable, and tastefully satisfying gadget that enables the clients to picture the most mainstream DevOps tools, characterize them, and sort each of those tools by usefulness and their pricing model. No matter what sort of tool you are looking for, it is just a one-stop look for the majority of the major DevOps tools branding whether it be an Open Source CI device or an Enterprise Testing tool.
#devops #devops periodic table #periodic table
1619536440
DevOps is a widely heard term in todayās market as the majority of the enterprises have opted to use the DevOps tools. Still many enterprises require a presentation for understanding the developments involved with using the DevOps tools. DevOps include social advancement which is a breakdown of the dividers and the storehouses between programming and activities with the tools and new techniques that empower these changes.
DevOps tools have speeded up the change in programming makers put up their applications and advance the applications for further sale to the public. The primary motivation for using DevOps tools as said by the majority of users is its quick development.
The Periodic Table of DevOps Tools is considered to be a dynamic, implant capable, and tastefully satisfying gadget that enables the clients to picture the most mainstream DevOps tools, characterize them, and sort each of those tools by usefulness and their pricing model. No matter what sort of tool you are looking for, it is just a one-stop look for the majority of the major DevOps tools branding whether it be an Open Source CI device or an Enterprise Testing tool.
#devops #devops periodic table #periodic table #devops tools
1661388540
A very simple package for accessing elements in the Periodic Table! š„
Since PeriodicTable is registered in Julia's General Registry, you can readily install it with
] add PeriodicTable
PeriodicTable.jl provides a Julia interface to a small database of element properties for all of the elements in the periodic table. In particular PeriodicTable
exports a global variable called elements
, which is a collection of Element
data structures.
julia> using PeriodicTable
julia> elements
Elements(ā¦119 elementsā¦):
H He
Li Be B C N O F Ne
Na Mg Al Si P S Cl Ar
K Ca Sc Ti V Cr Mn Fe Co Ni Cu Zn Ga Ge As Se Br Kr
Rb Sr Y Zr Nb Mo Tc Ru Rh Pd Ag Cd In Sn Sb Te I Xe
Cs Ba Hf Ta W Re Os Ir Pt Au Hg Tl Pb Bi Po At Rn
Fr Ra Rf Db Sg Bh Hs Mt Ds Rg Cn Nh Fl Mc Lv Ts Og
Uue
La Ce Pr Nd Pm Sm Eu Gd Tb Dy Ho Er Tm Yb Lu
Ac Th Pa U Np Pu Am Cm Bk Cf Es Fm Md No Lr
You can look up elements by name (case-insensitive) via elements["oxygen"]
, by symbol via elements[:O]
, or by number via elements[8]
, for example.
Each element has fields name
, appearance
, atomic_mass
, boil
, category
, color
, density
, discovered_by
, melt
, molar_heat
, named_by
, number
, period
, phase
, source
, spectral_img
, summary
, symbol
, xpos
, ypos
, shells
.
All physical quantities are unitful.
The data is pretty-printed when you look up an element in the Julia REPL. For example:
julia> elements["oxygen"]
Oxygen (O), number 8:
category: diatomic nonmetal
atomic mass: 15.999 u
density: 1.429 g/cm³
melting point: 54.36 K
boiling point: 90.188 K
phase: Gas
shells: [2, 6]
eā»-configuration: 1s² 2s² 2pā“
summary: Oxygen is a chemical element with symbol O and atomic number 8. It is a member of the chalcogen group on the periodic table and is a highly reactive nonmetal and oxidizing agent that readily forms compounds (notably oxides) with most elements. By mass, oxygen is the third-most abundant element in the universe, after hydrogen and helium.
discovered by: Carl Wilhelm Scheele
named by: Antoine Lavoisier
source: https://en.wikipedia.org/wiki/Oxygen
spectral image: https://en.wikipedia.org/wiki/File:Oxygen_spectre.jpg
Alternatively, you may want to get a list of elements,
julia> elements[1:4]
4-element Array{PeriodicTable.Element,1}:
Element(Hydrogen)
Element(Helium)
Element(Lithium)
Element(Beryllium)
A nice interactive visualization of the periodic table, based on PeriodicTable.jl, can be found here.
The data used for this package has been pulled up in parts from here. Some information has been (and will be) added over time.
Author: JuliaPhysics
Source Code: https://github.com/JuliaPhysics/PeriodicTable.jl
License: View license
1595209620
As a developer, I have experienced changes in app when it is in production and the records have grown up to millions. In this specific case if you want to alter a column using simple migrations that will not work because of the following reasons:
It is not so easy if your production servers are under heavy load and the database tables have 100 million rows. Because such a migration will run for some seconds or even minutes and the database table can be locked for this time period ā a no-go on a zero-downtime environment.
In this specific case you can use MySQLās algorithms: Online DDL operations. Thatās how you can do it in Laravel.
First of all create migration. For example I want to modify a columnās name the traditional migration will be:
Schema::table('users', function (Blueprint $table) {
$table->renameColumn('name', 'first_name');
});
Run the following command php artisan migrate āpretend this command will not run the migration rather it will print out itās raw sql:
ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL
Copy that raw sql, remove following code:
Schema::table('users', function (Blueprint $table) {
$table->renameColumn('name', 'first_name');
});
Replace it with following in migrations up method:
\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL');
Add desired algorithm, in my case query will look like this:
\DB::statement('ALTER TABLE users CHANGE name first_name VARCHAR(191) NOT NULL, ALGORITHM=INPLACE, LOCK=NONE;');
#laravel #mysql #php #alter heavy tables in production laravel #alter table in production laravel #alter tables with million of records in laravel #how to alter heavy table in production laravel #how to alter table in production larave #mysql online ddl operations
1660627020
JSONTables.jl
A package that provides a JSON integration with the Tables.jl interface, that is, it provides the jsontable
function as a way to treat a JSON object of arrays, or a JSON array of objects, as a Tables.jl-compatible source. This allows, among other things, loading JSON "tabular" data into a DataFrame
, or a JuliaDB.jl table, or written out directly as a csv file.
JSONTables.jl also provides two "write" functions, objecttable
and arraytable
, for taking any Tables.jl-comptabile source (e.g. DataFrame
, CSV.File
, etc.) and writing the table out either as a JSON object of arrays, or array of objects, respectively.
So in short:
# treat a json object of arrays or array of objects as a "table"
jtable = jsontable(json_source)
# turn json table into DataFrame
df = DataFrame(jtable)
# turn DataFrame back into json object of arrays
objecttable(df)
# turn DataFrame back into json array of objects
arraytable(df)
Author: JuliaData
Source Code: https://github.com/JuliaData/JSONTables.jl
License: MIT license