Dexter  Goodwin

Dexter Goodwin

1661922360

Tink: A Dependency Unwinder for Javascript

tink  

tink is an experimental package manager for JavaScript. Don't expect to be able to use this with any of your existing projects.

IN DEVELOPMENT

This package is still in development. Do not use it for production. It is missing major features and the interface should be considered extremely unstable.

If you're feeling adventurous, though, read ahead...

Usage

$ npx tink

Features

  • (mostly) npm-compatible project installation

Contributing

The tink team enthusiastically welcomes contributions and project participation! There's a bunch of things you can do if you want to contribute! The Contributor Guide has all the information you need for everything from reporting bugs to contributing entire new features. Please don't hesitate to jump in if you'd like to, or even ask us questions if something isn't clear.

Acknowledgements

Big thanks to Szymon Lisowiec for donating the tink package name on npm! This package was previously an error logger helper tool, but now it's a package manager runtime!

Commands

A Note About These Docs

The commands documented below are not normative, and may not reflect the current state of tink development. They are being written separately from the code itself, and may be entirely missing, or named something different, or behave completely different. tink is still under heavy development and you should expect everything to change without notice.

$ tink shell [options] [arguments]

  • Aliases: tink sh, tish

Starts an interactive tink shell. If -e or -p options are used, the string passed to them will be executed as a single line and the shell will exit immediately. If [arguments] is provided, it should be one or more executable JavaScript files, which will be loaded serially.

The interactive tink shell will automatically generate a .package-map.json describing all expected dependency files, and will fetch and make available any missing or corrupted data, as it's required. tink overrides most of Node's fs API to virtually load node_modules off a centralized cache without ever linking or extracting to node_modules itself.

By default, tink shell will automatically install and add any missing or corrupted dependencies that are found during the loading process. To disable this feature, use the --production or --offline options.

To get a physical node_modules/ directory to interact with, see tink unwind.

$ tink prepare [options] [package...]

  • Aliases: tink prep

Preloads declared dependencies. You can use this to make sure that by the time you use tink shell, all declared dependencies will already be cached and available, so there won't be any execution delay from inline fetching and repairing. If anything is missing or corrupted, it will be automatically re-fetched.

If one or more packages are passed in, they should be the names of packages already in package.json, and only the listed packages will be preloaded, instead of preloading all of them. If you want to add a new dependency, use tink add instead, which will also prepare the new dependencies for you (so tink prepare isn't necessary after a tink add).

$ tink exec [options] <pkg> [--] [args...]

  • Aliases: tink x, tx

Like npx, but for tink. Runs any binaries directly through tink.

$ tink unwind [options] [package...]

  • Aliases: tink extract, tink frog, tink unroll

Unwinds the project's dependencies into physical files in node_modules/, instead of using the fs overrides to load them. This "unwound" mode can be used to directly patch dependencies (for example, when debugging or preparing to fork), or to enable compatibility with non-tink-related tools.

If one or more [package...] arguments are provided, the unwinding process will only apply to those dependencies and their dependencies. In this case, package must be a direct dependency of your toplevel package. You cannot selectively unwind transitive dependencies, but you can make it so they're the only ones that stick around when you go back to tink mode. See tink wind for the corresponding command.

If --production, --only=<prod|dev>, or --also=<prod|dev> options are passed in, they can be used to limit which dependency types get unwound.

By default, this command will leave any files that were already in node_modules/ intact, so your patches won't be clobbered. To do a full reset, or a specific reset on a file, remove the specific file or all of node_modules/ manually before calling tink unwind

$ tink wind [options] [package...]

  • Aliases: tink roll, tink rewind, tink knit

Removes physical files from node_modules/ and configures a project to use "tink mode" for development -- a mode where dependency files are virtually loaded through fs API overrides off a central cache. This mode can greatly speed up install and start times, as well as conserve large amounts of space by sharing files (securely) across multiple projects.

If one or more [package...] arguments are provided, the wind-up process will only move the listed packages and any non-shared dependencies into the global cache to be served from there. Note that only direct dependencies can be requested this way -- there is no way to target specific transitive dependencies in tink wind, much like in tink unwind.

Any individual files in node_modules which do not match up with their standard hashes from their original packages will be left in place, unless the --wind-all option is used. For example, if you use tink unwind, then patch one of your dependencies with some console.log() calls, and you then do tink rewind, then the files you added console.log() to will remain in node_modules/, and be prioritized by tink when loading your dependencies. Any other files, including those for the same package, will be moved into the global cache and loaded from there as usual.

$ tink add [options] [spec...]

Downloads and installs each spec, which must be a valid dependency specifier parseable by npm-package-arg, and adds the newly installed dependency or dependencies to both package.json and package-lock.json, as well as updating .package-map.json as needed.

$ tink rm [options] [package...]

Removes each package, which should be a package name currently specified in package.json, from the current project's dependencies, updating package.json, package-lock.json, and .package-map.json as needed.

$ tink update [options] [spec...]

  • Aliases: tink up

Runs an interactive dependency update/upgrade UI where individual package updates can be selected. If one or more package arguments are passed in, the update prompts will be limited to packages in the tree matching those specifiers. The specifiers support full npm-package-arg specs and are used for matching existing dependencies, not the target versions to upgrade to.

If run outside of a TTY environment or if the --auto option is passed in, all dependencies, optionally limited to each named package, are updated to their maximum semver-compatible version, effectively simulating a fresh install of the project with the current declared package.json dependencies and no node_modules or package-lock.json present.

$ tink audit [options]

  • Aliases: tink odd, tink audi

Executes a full security scan of the project's dependencies, using the configured registry's audit service. --production, --only, and --also can be used to filter which dependency types are checked. --level can be used to specify the minimum vulnerability level that will make the command exit with a non-zero exit code (an error).

$ tink check-lock [options]

  • Aliases: tink lock

Verifies that package.json and package-lock.json are in sync. If --auto is specified, the inconsistency will be automatically corrected, using package.json as the source of truth.

$ tink check-licenses [options] [spec...]

By default, verifies that the current project has a valid "license" field, and that all dependencies (and transitive dependencies) have valid licenses configured.

If one or more spec arguments are provided, this behavior changes such that only the packages specified by the specs get verified according to current settings.

A list of detected licenses will be printed out. Use --json to get the licenses in a parseable format.

Additionally, two package.json fields can be used to further configure the license-checking behavior:

  • "blacklist": [licenses...] - Any detected licenses listed here will trigger an error for tink check-licenses. This takes precedence over "whitelist"
  • "whitelist": [licenses...] - Any detected licenses NOT listed in here will trigger an error.

$ tink lint [options]

  • Aliases: tink typecheck, tink type

Executes the configured lint and typecheck script(s) (in that order), or a default baseline linter will be used to report obvious syntax errors in the codebase's JavaScript.

$ tink build [options]

Executes the configured build script, if present, or executes silently.

$ tink clean [options]

Removes .package-map.json and executes the clean run-script, which should remove any artifacts generated by tink build.

$ tink test [options]

Executed the configured test run-script. Exits with an error code if no test script is configured.

$ tink check

Executes all verification-related scripts in the following sequence, grouping the output together into one big report:

  1. tink check-lock - verify that the package-lock.json and package.json are in sync, and that .package-map.json is up to date.
  2. tink audit - runs a security audit of the project's dependencies.
  3. tink check-licenses - verifies that the current project has a license configured, and that all dependencies have valid licenses, and that none of those licenses are blacklisted (or, if using a whitelist, that they are all in said whitelist -- see the tink check-licenses docs for details).
  4. tink lint - runs the configured linter, or a general, default linter that statically scans for syntax errors.
  5. tink build - if a build script is configured, the build will be executed to make sure it completes successfully -- otherwise, this step is skipped.
  6. tink test - runs the configured test suite. skipped if no tests configured, but a warning will be emitted.

The final report includes potential action items related to each step. Use --verbose to see more detailed output for each report.

$ tink publish [options] [tarball...]

Publishes the current package to the configured registry. The package will be turned into a tarball using tink pack, and the tarball will then be uploaded. This command will also print out a summary of tarball details, including the files that were included and the hashes for the tarball.

If One-Time-Passwords are configured on the registry and the terminal is a TTY, this command will prompt for an OTP token if --otp <token> is not used. If this happens outside of a TTY, the command will fail with an EOTP error.

Unlike npm publish, tink publish requires that package.json include a "files":[] array specifying which files will be included in the publish, otherwise the publish will fail with an error. .npmignore is obeyed, but does not remove the requirement for "files".

If --dry-run is used, all steps will be done, except the final data upload to the registry. Because the upload never happens, --dry-run can't be used to verify that publish credentials work.

If one or more tarball arguments are passed, they will be treated as npm-package-arg specifiers, fetched, and re-published. This is most useful with git repositories and local tarballs that have already been packaged up by tink pack

$ tink pack [options] [spec...]

Collects the current package into a tarball and writes it to ./<pkgname>-<pkgversion>.tgz. Also prints out a summary of tarball details, including the files that were included and the hashes for the tarball.

Unlike npm pack, tink pack requires that package.json include a "files":[] array specifying which files will be included in the publish, otherwise the publish will fail with an error. .npmignore is obeyed, but does not remove the requirement for "files".

If one or more spec arguments are passed, they will be treated as npm-package-arg specifiers, fetched, and their tarballed packages written to the current directory. This is most useful for fetching the tarballs of registry-hosted dependencies. For example: $ tink pack react@1.2.3 will write the tarball to ./react-1.2.3.tgz.

$ tink login

Use this command to log in to the current npm registry. This command may open a browser window.

$ tink logout

Use this command to remove any auth tokens for the current registry from your configuration.

Download Details:

Author: npm
Source Code: https://github.com/npm/tink 
License: View license

#javascript #npm 

What is GEEK

Buddha Community

Tink: A Dependency Unwinder for Javascript

Rahul Jangid

1622207074

What is JavaScript - Stackfindover - Blog

Who invented JavaScript, how it works, as we have given information about Programming language in our previous article ( What is PHP ), but today we will talk about what is JavaScript, why JavaScript is used The Answers to all such questions and much other information about JavaScript, you are going to get here today. Hope this information will work for you.

Who invented JavaScript?

JavaScript language was invented by Brendan Eich in 1995. JavaScript is inspired by Java Programming Language. The first name of JavaScript was Mocha which was named by Marc Andreessen, Marc Andreessen is the founder of Netscape and in the same year Mocha was renamed LiveScript, and later in December 1995, it was renamed JavaScript which is still in trend.

What is JavaScript?

JavaScript is a client-side scripting language used with HTML (Hypertext Markup Language). JavaScript is an Interpreted / Oriented language called JS in programming language JavaScript code can be run on any normal web browser. To run the code of JavaScript, we have to enable JavaScript of Web Browser. But some web browsers already have JavaScript enabled.

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Niraj Kafle

1589255577

The essential JavaScript concepts that you should understand

As a JavaScript developer of any level, you need to understand its foundational concepts and some of the new ideas that help us developing code. In this article, we are going to review 16 basic concepts. So without further ado, let’s get to it.

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Ajay Kapoor

1626321063

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Nat  Grady

Nat Grady

1670062320

How to Use Zapier with MongoDB

I’m a huge fan of automation when the scenario allows for it. Maybe you need to keep track of guest information when they RSVP to your event, or maybe you need to monitor and react to feeds of data. These are two of many possible scenarios where you probably wouldn’t want to do things manually.

There are quite a few tools that are designed to automate your life. Some of the popular tools include IFTTT, Zapier, and Automate. The idea behind these services is that given a trigger, you can do a series of events.

In this tutorial, we’re going to see how to collect Twitter data with Zapier, store it in MongoDB using a Realm webhook function, and then run aggregations on it using the MongoDB query language (MQL).

The Requirements

There are a few requirements that must be met prior to starting this tutorial:

  • A paid tier of Zapier with access to premium automations
  • A properly configured MongoDB Atlas cluster
  • A Twitter account

There is a Zapier free tier, but because we plan to use webhooks, which are premium in Zapier, a paid account is necessary. To consume data from Twitter in Zapier, a Twitter account is necessary, even if we plan to consume data that isn’t related to our account. This data will be stored in MongoDB, so a cluster with properly configured IP access and user permissions is required.

You can get started with MongoDB Atlas by launching a free M0 cluster, no credit card required.

While not necessary to create a database and collection prior to use, we’ll be using a zapier database and a tweets collection throughout the scope of this tutorial.

Understanding the Twitter Data Model Within Zapier

Since the plan is to store tweets from Twitter within MongoDB and then create queries to make sense of it, we should probably get an understanding of the data prior to trying to work with it.

We’ll be using the “Search Mention” functionality within Zapier for Twitter. Essentially, it allows us to provide a Twitter query and trigger an automation when the data is found. More on that soon.

As a result, we’ll end up with the following raw data:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "id": "1356701917603238000",
    "id_str": "1356701917603237888",
    "full_text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript",
    "truncated": false,
    "display_text_range": [0, 188],
    "metadata": {
        "iso_language_code": "en",
        "result_type": "recent"
    },
    "source": "<a href='https://about.twitter.com/products/tweetdeck' rel='nofollow'>TweetDeck</a>",
    "in_reply_to_status_id": null,
    "in_reply_to_status_id_str": null,
    "in_reply_to_user_id": null,
    "in_reply_to_user_id_str": null,
    "in_reply_to_screen_name": null,
    "user": {
        "id": "227546834",
        "id_str": "227546834",
        "name": "Nic Raboy",
        "screen_name": "nraboy",
        "location": "Tracy, CA",
        "description": "Advocate of modern web and mobile development technologies. I write tutorials and speak at events to make app development easier to understand. I work @MongoDB.",
        "url": "https://t.co/mRqzaKrmvm",
        "entities": {
            "url": {
                "urls": [
                    {
                        "url": "https://t.co/mRqzaKrmvm",
                        "expanded_url": "https://www.thepolyglotdeveloper.com",
                        "display_url": "thepolyglotdeveloper.com",
                        "indices": [0, 23]
                    }
                ]
            },
            "description": {
                "urls": ""
            }
        },
        "protected": false,
        "followers_count": 4599,
        "friends_count": 551,
        "listed_count": 265,
        "created_at": "Fri Dec 17 03:33:03 +0000 2010",
        "favourites_count": 4550,
        "verified": false
    },
    "lang": "en",
    "url": "https://twitter.com/227546834/status/1356701917603237888",
    "text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

The data we have access to is probably more than we need. However, it really depends on what you’re interested in. For this example, we’ll be storing the following within MongoDB:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "user": {
        "screen_name": "nraboy",
        "location": "Tracy, CA",
        "followers_count": 4599,
        "friends_count": 551
    },
    "text": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

Without getting too far ahead of ourselves, our analysis will be based off the followers_count and the location of the user. We want to be able to make sense of where our users are and give priority to users that meet a certain followers threshold.

Developing a Webhook Function for Storing Tweet Information with MongoDB Realm and JavaScript

Before we start connecting Zapier and MongoDB, we need to develop the middleware that will be responsible for receiving tweet data from Zapier.

Remember, you’ll need to have a properly configured MongoDB Atlas cluster.

We need to create a Realm application. Within the MongoDB Atlas dashboard, click the Realm tab.

MongoDB Realm Applications

For simplicity, we’re going to want to create a new application. Click the Create a New App button and proceed to fill in the information about your application.

From the Realm Dashboard, click the 3rd Party Services tab.

Realm Dashboard 3rd Party Services

We’re going to want to create an HTTP service. The name doesn’t matter, but it might make sense to name it Twitter based on what we’re planning to do.

Because we plan to work with tweet data, it makes sense to call our webhook function tweet, but the name doesn’t truly matter.

Realm Tweet Webhook

With the exception of the HTTP Method, the defaults are fine for this webhook. We want the method to be POST because we plan to create data with this particular webhook function. Make note of the Webhook URL because it will be used when we connect Zapier.

The next step is to open the Function Editor so we can add some logic behind this function. Add the following JavaScript code:

exports = function (payload, response) {

    const tweet = EJSON.parse(payload.body.text());

    const collection = context.services.get("mongodb-atlas").db("zapier").collection("tweets");

    return collection.insertOne(tweet);

};

In the above code, we are taking the request payload, getting a handle to the tweets collection within the zapier database, and then doing an insert operation to store the data in the payload.

There are a few things to note in the above code:

  1. We are not validating the data being sent in the request payload. In a realistic scenario, you’d probably want some kind of validation logic in place to be sure about what you’re storing.
  2. We are not authenticating the user sending the data. In this example, we’re trusting that only Zapier knows about our URL.
  3. We aren’t doing any error handling.

When we call our function, a new document should be created within MongoDB.

By default, the function will not deploy when saving. After saving, make sure to review and deploy the changes through the notification at the top of the browser window.

Creating a “Zap” in Zapier to Connect Twitter to MongoDB

So, we know the data we’ll be working with and we have a MongoDB Realm webhook function that is ready for receiving data. Now, we need to bring everything together with Zapier.

For clarity, new Twitter matches will be our trigger in Zapier, and the webhook function will be our event.

Within Zapier, choose to create a new “Zap,” which is an automation. The trigger needs to be a Search Mention in Twitter, which means that when a new Tweet is detected using a search query, our events happen.

Zapier Twitter Search Mention

For this example, we’re going to use the following Twitter search query:

url:developer.mongodb.com -filter:retweets filter:safe lang:en -from:mongodb -from:realm

The above query says that we are looking for tweets that include a URL to developer.mongodb.com. The URL doesn’t need to match exactly as long as the domain matches. The query also says that we aren’t interested in retweets. We only want original tweets, they have to be in English, and they have to be detected as safe for work.

In addition to the mentioned search criteria, we are also excluding tweets that originate from one of the MongoDB accounts.

In theory, the above search query could be used to see what people are saying about the MongoDB Developer Hub.

With the trigger in place, we need to identify the next stage of the automation pipeline. The next stage is taking the data from the trigger and sending it to our Realm webhook function.

Zapier to Realm Webhook

As the event, make sure to choose Webhooks by Zapier and specify a POST request. From here, you’ll be prompted to enter your Realm webhook URL and the method, which should be POST. Realm is expecting the payload to be JSON, so it is important to select JSON within Zapier.

We have the option to choose which data from the previous automation stage to pass to our webhook. Select the fields you’re interested in and save your automation.

The data I chose to send looks like this:

{
    "created_at": "Tue Feb 02 20:31:58 +0000 2021",
    "username": "nraboy",
    "location": "Tracy, CA",
    "follower_count": "4599",
    "following_count": "551",
    "message": "In case anyone is interested in learning about how to work with streaming data using Node.js, I wrote a tutorial about it on the @MongoDB Developer Hub. https://t.co/Dxt80lD8xj #javascript"
}

The fields do not match the original fields brought in by Twitter. It is because I chose to map them to what made sense for me.

When deploying the Zap, anytime a tweet is found that matches our query, it will be saved into our MongoDB cluster.

Analyzing the Twitter Data in MongoDB with an Aggregation Pipeline

With tweet data populating in MongoDB, it’s time to start querying it to make sense of it. In this fictional example, we want to know what people are saying about our Developer Hub and how popular these individuals are.

To do this, we’re going to want to make use of an aggregation pipeline within MongoDB.

Take the following, for example:

[
    {
        "$addFields": {
            "follower_count": {
                "$toInt": "$follower_count"
            },
            "following_count": {
                "$toInt": "$following_count"
            }
        }
    }, {
        "$match": {
            "follower_count": {
                "$gt": 1000
            }
        }
    }, {
        "$group": {
            "_id": {
                "location": "$location"
            },
            "location": {
                "$sum": 1
            }
        }
    }
]

There are three stages in the above aggregation pipeline.

We want to understand the follower data for the individual who made the tweet, but that data comes into MongoDB as a string rather than an integer. The first stage of the pipeline takes the follower_count and following_count fields and converts them from string to integer. In reality, we are using $addFields to create new fields, but because they have the same name as existing fields, the existing fields are replaced.

The next stage is where we want to identify people with more than 1,000 followers as a person of interest. While people with fewer followers might be saying great things, in this example, we don’t care.

After we’ve filtered out people by their follower count, we do a group based on their location. It might be valuable for us to know where in the world people are talking about MongoDB. We might want to know where our target audience exists.

The aggregation pipeline we chose to use can be executed with any of the MongoDB drivers, through the MongoDB Atlas dashboard, or through the CLI.

Conclusion

You just saw how to use Zapier with MongoDB to automate certain tasks and store the results as documents within the NoSQL database. In this example, we chose to store Twitter data that matched certain criteria, later to be analyzed with an aggregation pipeline. The automations and analysis options that you can do are quite limitless.

If you enjoyed this tutorial and want to get engaged with more content and like-minded developers, check out the MongoDB Community.

This content first appeared on MongoDB.

Original article source at: https://www.thepolyglotdeveloper.com/

#mongodb #zapier