Madyson  Moore

Madyson Moore

1665766200

Md2nb: Markdown to Wolfram Notebook Converter in Rust

md2nb 

md2nb is a command-line tool for converting Markdown files into Wolfram Notebooks.

Diagram showing md2nb conversion of Markdown files to Wolfram Notebooks

Usage

md2nb is a command-line tool. After installing md2nb, it can be used to convert a .md file to a .nb:

$ md2nb <INPUT>.md <OUTPUT>.nb

For example, to convert this project's README.md file into a Wolfram Notebook, execute:

$ md2nb README.md README.nb

Features

md2nb converts .md files into Wolfram .nb files.

Markdown constructs are converted into corresponding standard Wolfram Notebook representations.

Most CommonMark features are supported, including:

  • Text styles like emphasis and italics
  • Links
  • Headers
  • Bulleted lists
  • Code blocks
  • Block quotes
  • Tables
  • Horizontal rules

Additionally, some Markdown features are converted into Wolfram Notebook representations that are more interactive than typical rendered Markdown:

  • Code blocks containing code written in a language supported by ExternalEvaluate will be converted to external language cells, which can be executed directly within the Wolfram Notebook.

Examples

See the 'Kitchen Sink' example, which includes samples of all Markdown features currently supported by md2nb.

Installation

Using cargo

md2nb can be installed using cargo (the Rust package manager) by executing:

$ cargo install md2nb

This will install the latest version of md2nb from crates.io.

License

Licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.


Download Details:

Author: ConnorGray
Source Code: https://github.com/ConnorGray/md2nb

License: Apache-2.0, MIT licenses found

#rust 

What is GEEK

Buddha Community

Md2nb: Markdown to Wolfram Notebook Converter in Rust

Serde Rust: Serialization Framework for Rust

Serde

*Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.*

You may be looking for:

Serde in action

Click to show Cargo.toml. Run this code in the playground.

[dependencies]

# The core APIs, including the Serialize and Deserialize traits. Always
# required when using Serde. The "derive" feature is only required when
# using #[derive(Serialize, Deserialize)] to make Serde work with structs
# and enums defined in your crate.
serde = { version = "1.0", features = ["derive"] }

# Each data format lives in its own crate; the sample code below uses JSON
# but you may be using a different one.
serde_json = "1.0"

 

use serde::{Serialize, Deserialize};

#[derive(Serialize, Deserialize, Debug)]
struct Point {
    x: i32,
    y: i32,
}

fn main() {
    let point = Point { x: 1, y: 2 };

    // Convert the Point to a JSON string.
    let serialized = serde_json::to_string(&point).unwrap();

    // Prints serialized = {"x":1,"y":2}
    println!("serialized = {}", serialized);

    // Convert the JSON string back to a Point.
    let deserialized: Point = serde_json::from_str(&serialized).unwrap();

    // Prints deserialized = Point { x: 1, y: 2 }
    println!("deserialized = {:?}", deserialized);
}

Getting help

Serde is one of the most widely used Rust libraries so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

Download Details:
Author: serde-rs
Source Code: https://github.com/serde-rs/serde
License: View license

#rust  #rustlang 

Madyson  Moore

Madyson Moore

1665766200

Md2nb: Markdown to Wolfram Notebook Converter in Rust

md2nb 

md2nb is a command-line tool for converting Markdown files into Wolfram Notebooks.

Diagram showing md2nb conversion of Markdown files to Wolfram Notebooks

Usage

md2nb is a command-line tool. After installing md2nb, it can be used to convert a .md file to a .nb:

$ md2nb <INPUT>.md <OUTPUT>.nb

For example, to convert this project's README.md file into a Wolfram Notebook, execute:

$ md2nb README.md README.nb

Features

md2nb converts .md files into Wolfram .nb files.

Markdown constructs are converted into corresponding standard Wolfram Notebook representations.

Most CommonMark features are supported, including:

  • Text styles like emphasis and italics
  • Links
  • Headers
  • Bulleted lists
  • Code blocks
  • Block quotes
  • Tables
  • Horizontal rules

Additionally, some Markdown features are converted into Wolfram Notebook representations that are more interactive than typical rendered Markdown:

  • Code blocks containing code written in a language supported by ExternalEvaluate will be converted to external language cells, which can be executed directly within the Wolfram Notebook.

Examples

See the 'Kitchen Sink' example, which includes samples of all Markdown features currently supported by md2nb.

Installation

Using cargo

md2nb can be installed using cargo (the Rust package manager) by executing:

$ cargo install md2nb

This will install the latest version of md2nb from crates.io.

License

Licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.


Download Details:

Author: ConnorGray
Source Code: https://github.com/ConnorGray/md2nb

License: Apache-2.0, MIT licenses found

#rust 

Awesome  Rust

Awesome Rust

1654894080

Serde JSON: JSON Support for Serde Framework

Serde JSON

Serde is a framework for serializing and deserializing Rust data structures efficiently and generically.

[dependencies]
serde_json = "1.0"

You may be looking for:

JSON is a ubiquitous open-standard format that uses human-readable text to transmit data objects consisting of key-value pairs.

{
    "name": "John Doe",
    "age": 43,
    "address": {
        "street": "10 Downing Street",
        "city": "London"
    },
    "phones": [
        "+44 1234567",
        "+44 2345678"
    ]
}

There are three common ways that you might find yourself needing to work with JSON data in Rust.

  • As text data. An unprocessed string of JSON data that you receive on an HTTP endpoint, read from a file, or prepare to send to a remote server.
  • As an untyped or loosely typed representation. Maybe you want to check that some JSON data is valid before passing it on, but without knowing the structure of what it contains. Or you want to do very basic manipulations like insert a key in a particular spot.
  • As a strongly typed Rust data structure. When you expect all or most of your data to conform to a particular structure and want to get real work done without JSON's loosey-goosey nature tripping you up.

Serde JSON provides efficient, flexible, safe ways of converting data between each of these representations.

Operating on untyped JSON values

Any valid JSON data can be manipulated in the following recursive enum representation. This data structure is serde_json::Value.

enum Value {
    Null,
    Bool(bool),
    Number(Number),
    String(String),
    Array(Vec<Value>),
    Object(Map<String, Value>),
}

A string of JSON data can be parsed into a serde_json::Value by the serde_json::from_str function. There is also from_slice for parsing from a byte slice &[u8] and from_reader for parsing from any io::Read like a File or a TCP stream.

use serde_json::{Result, Value};

fn untyped_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into serde_json::Value.
    let v: Value = serde_json::from_str(data)?;

    // Access parts of the data by indexing with square brackets.
    println!("Please call {} at the number {}", v["name"], v["phones"][0]);

    Ok(())
}

The result of square bracket indexing like v["name"] is a borrow of the data at that index, so the type is &Value. A JSON map can be indexed with string keys, while a JSON array can be indexed with integer keys. If the type of the data is not right for the type with which it is being indexed, or if a map does not contain the key being indexed, or if the index into a vector is out of bounds, the returned element is Value::Null.

When a Value is printed, it is printed as a JSON string. So in the code above, the output looks like Please call "John Doe" at the number "+44 1234567". The quotation marks appear because v["name"] is a &Value containing a JSON string and its JSON representation is "John Doe". Printing as a plain string without quotation marks involves converting from a JSON string to a Rust string with as_str() or avoiding the use of Value as described in the following section.

The Value representation is sufficient for very basic tasks but can be tedious to work with for anything more significant. Error handling is verbose to implement correctly, for example imagine trying to detect the presence of unrecognized fields in the input data. The compiler is powerless to help you when you make a mistake, for example imagine typoing v["name"] as v["nmae"] in one of the dozens of places it is used in your code.

Parsing JSON as strongly typed data structures

Serde provides a powerful way of mapping JSON data into Rust data structures largely automatically.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Person {
    name: String,
    age: u8,
    phones: Vec<String>,
}

fn typed_example() -> Result<()> {
    // Some JSON input data as a &str. Maybe this comes from the user.
    let data = r#"
        {
            "name": "John Doe",
            "age": 43,
            "phones": [
                "+44 1234567",
                "+44 2345678"
            ]
        }"#;

    // Parse the string of data into a Person object. This is exactly the
    // same function as the one that produced serde_json::Value above, but
    // now we are asking it for a Person as output.
    let p: Person = serde_json::from_str(data)?;

    // Do things just like with any other Rust data structure.
    println!("Please call {} at the number {}", p.name, p.phones[0]);

    Ok(())
}

This is the same serde_json::from_str function as before, but this time we assign the return value to a variable of type Person so Serde will automatically interpret the input data as a Person and produce informative error messages if the layout does not conform to what a Person is expected to look like.

Any type that implements Serde's Deserialize trait can be deserialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Deserialize)].

Once we have p of type Person, our IDE and the Rust compiler can help us use it correctly like they do for any other Rust code. The IDE can autocomplete field names to prevent typos, which was impossible in the serde_json::Value representation. And the Rust compiler can check that when we write p.phones[0], then p.phones is guaranteed to be a Vec<String> so indexing into it makes sense and produces a String.

The necessary setup for using Serde's derive macros is explained on the Using derive page of the Serde site.

Constructing JSON values

Serde JSON provides a json! macro to build serde_json::Value objects with very natural JSON syntax.

use serde_json::json;

fn main() {
    // The type of `john` is `serde_json::Value`
    let john = json!({
        "name": "John Doe",
        "age": 43,
        "phones": [
            "+44 1234567",
            "+44 2345678"
        ]
    });

    println!("first phone number: {}", john["phones"][0]);

    // Convert to a string of JSON and print it out
    println!("{}", john.to_string());
}

The Value::to_string() function converts a serde_json::Value into a String of JSON text.

One neat thing about the json! macro is that variables and expressions can be interpolated directly into the JSON value as you are building it. Serde will check at compile time that the value you are interpolating is able to be represented as JSON.

let full_name = "John Doe";
let age_last_year = 42;

// The type of `john` is `serde_json::Value`
let john = json!({
    "name": full_name,
    "age": age_last_year + 1,
    "phones": [
        format!("+44 {}", random_phone())
    ]
});

This is amazingly convenient, but we have the problem we had before with Value: the IDE and Rust compiler cannot help us if we get it wrong. Serde JSON provides a better way of serializing strongly-typed data structures into JSON text.

Creating JSON by serializing data structures

A data structure can be converted to a JSON string by serde_json::to_string. There is also serde_json::to_vec which serializes to a Vec<u8> and serde_json::to_writer which serializes to any io::Write such as a File or a TCP stream.

use serde::{Deserialize, Serialize};
use serde_json::Result;

#[derive(Serialize, Deserialize)]
struct Address {
    street: String,
    city: String,
}

fn print_an_address() -> Result<()> {
    // Some data structure.
    let address = Address {
        street: "10 Downing Street".to_owned(),
        city: "London".to_owned(),
    };

    // Serialize it to a JSON string.
    let j = serde_json::to_string(&address)?;

    // Print, write to a file, or send to an HTTP server.
    println!("{}", j);

    Ok(())
}

Any type that implements Serde's Serialize trait can be serialized this way. This includes built-in Rust standard library types like Vec<T> and HashMap<K, V>, as well as any structs or enums annotated with #[derive(Serialize)].

Performance

It is fast. You should expect in the ballpark of 500 to 1000 megabytes per second deserialization and 600 to 900 megabytes per second serialization, depending on the characteristics of your data. This is competitive with the fastest C and C++ JSON libraries or even 30% faster for many use cases. Benchmarks live in the serde-rs/json-benchmark repo.

Getting help

Serde is one of the most widely used Rust libraries, so any place that Rustaceans congregate will be able to help you out. For chat, consider trying the #rust-questions or #rust-beginners channels of the unofficial community Discord (invite: https://discord.gg/rust-lang-community), the #rust-usage or #beginners channels of the official Rust Project Discord (invite: https://discord.gg/rust-lang), or the #general stream in Zulip. For asynchronous, consider the [rust] tag on StackOverflow, the /r/rust subreddit which has a pinned weekly easy questions post, or the Rust Discourse forum. It's acceptable to file a support issue in this repo, but they tend not to get as many eyes as any of the above and may get closed without a response after some time.

No-std support

As long as there is a memory allocator, it is possible to use serde_json without the rest of the Rust standard library. This is supported on Rust 1.36+. Disable the default "std" feature and enable the "alloc" feature:

[dependencies]
serde_json = { version = "1.0", default-features = false, features = ["alloc"] }

For JSON support in Serde without a memory allocator, please see the serde-json-core crate.

Link: https://crates.io/crates/serde_json

#rust  #rustlang  #encode   #json 

Rajat Rajput

1625301328

OST to PST Converter Free to Convert OST to PST Online

When the exchange server is synchronised with MS Outlook then, automatically a copy of its mailboxes will be generated in OST (Offline Storage Table) file format. The user can access OST data in the offline mode and work on them. The changes will get updated when the internet connectivity is re-established. OST files cannot be accessed in the other system or remote system. So to access the OST files in another system Outlook, then convert Outlook OST to PST format. Due to various reasons for which users’ want to convert OST to PST file format such as the Exchange might face some technical issues, downtime or crash. How to convert OST to PST in Outlook 2016, 2013, 2010? Well, in this blog, we will discuss both manual as well as the professional best OST to PST Converter online solution.
For better understanding of users’, we have listed some common reasons below.

Why There is a Need to Export OST to PST Outlook?

Before providing methods to the query “how to convert OST file to PST in outlook 2016”, first understand why users’ need to convert OST to PST. Some of the basic reasons are provided below.

  • When the Exchange server is under maintenance.
  • Accidental deletion of the Exchange server account.
  • Virus or Malware attacks.
  • Power Failures or intrusions by malicious software.

These are a few reasons for Outlook OST to PST conversion. Now let’s proceed ahead to different methods to convert OST to PST online.

How to Convert OST to PST in Outlook 2016 Manually?

Manual strategies are cost-effective methods and here, we will discuss the complete manual steps for OST to PST conversion. Before starting the steps, it is suggested to create a backup copy of the original data as there might be a risk of human error that can ultimately lead to severe data loss. How to convert OST to PST manually? Follow the methods provided below -

Method 1: Import/ Export Feature

  1. Open your Microsoft Outlook program.
  2. Click on the File tab.
  3. Select the Import/Export option.
  4. Click on Export to a file.
  5. Press the Next button.
  6. Now Select the Personal File folder (.pst).
  7. Click on the Parent root.
  8. Check on the include subfolders
  9. Click on browse and navigate to the path to save the resultant data.
  10. Click on the finish button.

Method 2: Use Outlook Archive Feature

  1. Sign-in to Microsoft Outlook.
  2. Go to the File section
  3. Click on Options
  4. Now, click on the Advanced section
  5. Click on Auto Archive settings…
  6. Navigate to the path to save the archived files.
  7. Click on the OK button.

Drawbacks

  • Manual Processes are lengthy and more time-consuming.
  • Need connectivity with the Exchange server.
  • Unable to export corrupt OST data.
  • Outlook application installation is required.
  • Feasible for small sized OST files only.
  • High risk of data loss.

How to Convert OST to PST in Outlook 2016 Using DRS OST to PST Converter

To avoid all the limitations that we have already seen above with the conventional manual techniques, users can opt for a well known and reliable automated method for conversion. There are numerous third-party solutions available to convert OST to PST, however it is suggested to use a trusted software. Using the smart DRS Best OST to PST Converter online utility that allows to export OST to PST, MBOX, MSG, EML, PDF, CSV, HTML, Gmail, Yandex mail, Yahoo, Office 365, etc. It can easily open corrupt OST files and convert them to healthy PST. The tool even allows users to smoothly export all the mailbox items like attachments, calendar, contacts, journals, tasks, etc. There are no file size restrictions and no risk of severe data loss. The advanced software is compatible with all versions of Mac and Windows. The free OST to PST Converter online version allows to export 50 emails for free.

Conclusion

Above in this blog, we have discussed the recommended solutions by experts on the query “how to convert OST to PST in Outlook 2016”. At the end of this article, we can conclude that manual strategies have several limitations, so it is suggested to use the well known DRS OST to PST Converter for an effective, accurate and effortless conversion.

#how to convert ost file to pst in outlook 2016 #how to convert ost to pst online #how to convert ost to pst manually #convert ost to pst #ost to pst converter #outlook ost to pst

Rust Lang Course For Beginner In 2021: Guessing Game

 What we learn in this chapter:
- Rust number types and their default
- First exposure to #Rust modules and the std::io module to read input from the terminal
- Rust Variable Shadowing
- Rust Loop keyword
- Rust if/else
- First exposure to #Rust match keyword

=== Content:
00:00 - Intro & Setup
02:11 - The Plan
03:04 - Variable Secret
04:03 - Number Types
05:45 - Mutability recap
06:22 - Ask the user
07:45 - First intro to module std::io
08:29 - Rust naming conventions
09:22 - Read user input io:stdin().read_line(&mut guess)
12:46 - Break & Understand
14:20 - Parse string to number
17:10 - Variable Shadowing
18:46 - If / Else - You Win, You Loose
19:28 - Loop
20:38 - Match
23:19 - Random with rand
26:35 - Run it all
27:09 - Conclusion and next episode

#rust