React in a Legacy App

I am working on a relatively old legacy web app. It’s a very complex system, and was built upon jQuery and uses requirejs for module loading. I have been slowly updating it to use ES5+ features and React. In particular, working with React in this app has been a bit painful. This app, you see, doesn’t have a build environment, so using webpack and babel aren’t available, at least not in the standard way. With a great deal of effort, it certainly can be made to work with a build environment, but my intention is to spend my energy on cleaning up the code and, when that task is complete, bringing in a standard build system. Ah, that will be great.

But, at least for today, I want to add some React code. I’ve done it before in this app, but since I have no build system, I’ve used React.createElement(). If you’ve tried to build anything more than a trivial Component using React.createElement(), you know that it gets old, fast.

So I want to just JSX, naturally. But with no build system, I wasn’t sure how to proceed. There are plenty of examples on how to use babel standalone and mark your script tags as "text/babel" to have your JSX code converted to JS on the fly. But, a couple problems. First, I’m using requirejs, and it doesn’t want to mark only some script tags as "text/babel" (it can mark all or none). I’ve even gone so far as modifying requirejs to only mark certain script tags as "text/babel" but that leads to the next problem: babel standalone doesn’t seem to compile the scripts imported by requirejs. I’m sure there’s a way, but I gave up on that approach.

What I really wanted was something that would just compile JSX files into JS, so I could write complex React Components and not worry about it.

I found some examples for using browserify and babel to basically do what a build system would do, but it ends up creating massive JS files with all kinds of transpiled code. Clearly I was doing this wrong.

I finally found that I can use a basic babel transformFile() call with some relatively simple configuration that mainly just compiles the React JSX into React JS with React.createElement() calls, and really no other change to my code.

I wrote a “watcher” script for this purpose, and now just keep it running in my IDE while I work:

 const args = require('minimist')(process.argv.slice(2));
 const fs = require("fs/promises");
 const path = require("path");
 const chokidar = require("chokidar");
 const babel = require("@babel/core");
 const options = {
   ignored: /(^|[\/\\])\../
 async function compile(src) {
   return new Promise((resolve, reject) => {
     const info = path.parse(src);
     const dest = path.join(info.dir, `${}.js`);
     babel.transformFile(src, {}, async (error, result) => {
       if (error) { return reject(error) }
       await fs.writeFile(dest, result.code);
       console.log(`compiled ${src} -> ${dest}`);
 async function remove(src) {
   const info = path.parse(src);
   const dest = path.join(info.dir, `${}.js`);
     .then(() => {
       console.log(`removed ${dest}`);
     .catch(error => {
       // ignore
 (async () => {'**/*.jsx', options).on('all', async (event, path) => {
     if (event === "add" || event === "change") {
       await compile(path);
     if (event === "unlink" && args.delete) {
       await remove(path);

The babel configuration file (babel.config.json) looks like this:

   "presets": [
         "targets": {
           "edge": "17",
           "firefox": "60",
           "chrome": "67",
           "safari": "11.1"
         "useBuiltIns": "usage",
         "corejs": "3.6.5"
   "plugins": ["@babel/plugin-syntax-class-properties"]

For packages, I’ve installed these in my package.json file:

chokidar minimist 

Jupyter Widgets: Sending Custom Event To Frontend From Backend

Jupyter Widgets can have a separate frontend and backend component. Sometimes, you need to send a message from one to the other. This example shows the basics on sending a message from the backend to the frontend.

In your Widget’s frontend (JavaScript) code, listen for the custom event from the backend:

    render: function() {
        this.model.on('msg:custom', this.customEvent.bind(this));
    customEvent: function(event) {
        switch (event.type) {
            case 'my_important_event':

Now, in the Widget’s backend (Python) code, send the message as needed:

    def send_message_to_frontend(self):
        self.send({"method": "custom", "type": "my_important_event", "value": "blue"})

Jupyter Widgets: Sending Custom Event To Backend From Frontend

Jupyter Widgets can have a separate frontend and backend component. Sometimes, you need to send a message from one to the other. This example shows the basics on sending a message from the frontend to the backend.

In your Widget’s backend (Python) code, listen for the custom event from the frontend:

    def __init__(self, **kwargs):
    def _handle_custom_msg(self, content, buffers):
        if content['event'] == 'another_important_event':

Now, in the Widget’s frontend (Javascript) code, send the message as needed:

    sendMessageToBackend: function() {
        this.model.send({event: 'another_important_event', value: 'green'});

Jupyter Widgets: Finding My Cell Object

When writing a custom Jupyter Widget, sometimes you need to know the Cell (CodeCell, usually) that your Widget is running in. You can get a list of all Cells from the Notebook object in Javascript, but finding your Cell isn’t exactly that straight-forward.

Fortunately, it isn’t that hard to determine your Cell, since you can find the container element for your Widget, and then loop through all Cells in the Notebook to see which one you are in:

const container = this.$el.parents('.cell');
const cell = this.notebook.get_cells().find(it =>;

If all goes well, cell will contain your Cell object.

Parsing CSV and TSV Files


A very common file format for transferring data is the Comma (or TAB) Separated Value file. These formats appear simple, but have several complications that make implementing a CSV/TSV parser slightly more challenging than just breaking a row of text by its separator.

It’s probably best to start with some definitions before diving into any details. In this file format, which is a text file where each line of text is like a row in a spreadsheet, and each of those rows is made up of columns.

The generally accepted practice is to call the rows Records, and the columns Fields. The first line is typically included, but not required, and contains the Field names.

basic parsing

Fields are separated by their separator character, which is a comma for a CSV and a TAB for a TSV:


This works perfectly fine for a TSV, since the value in a Field probably wouldn’t contain a TAB character. But what about a CSV? It seems reasonable that the value in a Field could have one or more commas.

1,cat,Meow,warm, purring, fuzzy,small
2,dog,Bark,loyal, funny, protective,medium
3,cow,Moo,tippable, clears grass,large

There’s no reasonable way to parse the Fields in this file (note that Field names in the first row, if included, are not required to match the Record Fields). The solution is to require double quotes around a Field that contains a comma:

1,cat,Meow,"warm, purring, fuzzy",small
2,dog,Bark,"loyal, funny, protective",medium
3,cow,Moo,"tippable, clears grass",large

Now we can parse this file, since the double quotes indicate the beginning and end of a Field. If we see a starting double quote, we can just keep reading until we see a closing double quote.

embedded double quotes

But what about double quotes themselves? It’s certainly common to see double quotes in different situations in a Field. Text in the field could be quoted, or a double quote could be used to mean inches. If we used the above logic of using an opening and closing double quote to know when a Field begins and ends, something like this will cause trouble:

2,round clock,8"x8"
3,used laptop,just "like new!"

The answer is to “escape” the double quotes in some way, and the decision was to use double double quotes. However, this causes its own problem, if we’re using double quotes to determine if commas are part of a Field, or if they are the separator between Fields, how can we tell? The answer, again, is to require double quotes around a Field that contains a double quote (or, more accurately now, an escaped double quote):

2,round clock,"8""x8"""
3,used laptop,"just ""like new!"""

This use of escaping double quotes, and requiring double quotes around a Field that contains double quotes is common to both CSV and TSV.

embedded newlines or carriage returns

The final major thing to consider when parsing a CSV or TSV is that a Field could contain a newline or carriage return character:

1,shoe,these are fine shoes
2,round clock,features:
2 hands
round, 8"
maple wood
3,used laptop,technical specs:
2048 Neurobit 1098X3 CPU
12 Parsec pseudo-drive
15" screen

Since a newline (or carriage return) should indicate the end of the current Field and also the completion of the current Record, how do we deal with them as part of a Field? I’m sure you’ve guessed that double quotes are involved, and they are:

1,shoe,these are fine shoes
2,round clock,"features:
2 hands
round, 8""
maple wood"
3,used laptop,"technical specs:
2048 Neurobit 1098X3 CPU
12 Parsec pseudo-drive
15"" screen"

Notice that there are also escaped double quotes and commas in these Fields as well. The opening and closing double quotes allow for those in the Field.

other consideration

In general, this covers the major issues faced when parsing a CSV or TSV file. Note that a TSV can also allow for some special escaped characters:

characterescaped value
newline (\n character)\n as two characters
carriage return (\r character)\r as two characters
tab (\t character)\t as two characters
backslash\\ as two characters

Tomcat: Enabling SSL

Usually, when you get your SSL certificates, they are .crt, .key, and .ca-bundle files. These work fine for Apache’s HTTP server, but Apache’s Tomcat server needs these converted into a .jks (Java Key Store), and the Tomcat configuration set up to use that key store. To simplify the conversion, here is a shell script to perform the steps, under the assumption that the .crt, .key, and .ca-bundle files all have the same prefix.

if [ "$1" = "" ]; then
  echo ""
  echo "  usage: $0 <file-prefix> <password>"
  echo ""
  echo "  This tool requires that all files have the same prefix, and the .crt, .key, and .ca-bundle files exist."
  echo ""
  echo "  For example, if your files are named,,, you would do:"
  echo ""
  echo "    $0 mySekretPasswd"
  echo ""
  exit 1
echo ""
echo "  Generating JKS file for $1..."
echo ""
echo "----------------------------------------------------------"
openssl pkcs12 -export -in $1.crt -inkey $1.key -name $1 -out $1.p12 -passout pass:$2
keytool -importkeystore -deststorepass $2 -destkeystore $1.jks -srckeystore $1.p12 -srcstoretype PKCS12 -srcstorepass $2
keytool -import -alias bundle -trustcacerts -file $ -keystore $1.jks -storepass $2
prefix_alias=`keytool -list -v -keystore $1.jks -storepass $2 | grep -i alias | grep $1`
if [ "$prefix_alias" = "" ]; then
  echo ""
  echo "  ** something seems to have gone wrong, $1 not found in aliases"
  echo ""
  exit 1
echo "----------------------------------------------------------"
echo ""
echo "  JKS file created."
echo ""
echo "  Copy $1.jks to Tomcat's ssl directory, typically something like /etc/tomcat8/ssl/$1.jks"
echo ""
echo "  Add or Update the <Connector> entries in Tomcat's server.xml to be something like:"
echo ""
echo "    <Connector port=\"8443\" protocol=\"org.apache.coyote.http11.Http11NioProtocol\" maxThreads=\"150\" SSLEnabled=\"true\" scheme=\"https\" secure=\"true\" clientAuth=\"false\" sslProtocol=\"TLS\" keystoreFile=\"/etc/tomcat8/ssl/$1.jks\" keystoreType=\"JKS\" keystorePass=\"$2\" keyAlias=\"$1\" />"
echo "    <Connector port=\"8009\" protocol=\"AJP/1.3\" redirectPort=\"8443\" />"
echo "" 

An example of using the tool, if your certificate files all start with

./ mySekretPasswd 

Ubuntu 19.10 (and 20.04): Setting Up Time Machine

Setting up an Ubuntu machine to act as an Apple Time Machine server is surprisingly simple. This example uses a directory on the boot drive (/srv/netatalk/time-machine), but it’s more likely that you want to use a directory on a large disk.
Here are the steps…

Install the needed packages:

sudo apt install netatalk avahi-daemon

Edit the netatalk config file:

sudo vi /etc/netatalk/afp.conf

Add a section for your Time Machine:

[Time Machine]
  path = /srv/netatalk/time-machine
  time machine = yes

Create a directory to act as the Time Machine drive:

sudo mkdir -p /srv/netatalk/time-machine
sudo chown nobody:nogroup /srv/netatalk/time-machine
sudo chmod 777 /srv/netatalk/time-machine

Restart netatalk:

sudo service netatalk restart

Now, on your Mac, you should be able to open the Time Machine settings in System Preferences and use Select Disk… to pick your new Time Machine backup drive.

Update for Ubuntu 20.04 and other notes

Since I first wrote this, I have updated to Ubuntu 20.04 and everything still seems to work. However, I never made it clear that you must make sure your backup drive is available and connected on your Mac before you can use it as a Time Machine backup drive.

Once your drive is set up under Ubuntu, go to your Mac and open a Finder window. Under the Network section in the sidebar, you should see your Ubuntu machine listed. Double-click on the machine name, and you should see any shared folders on the machine. You may have to click on the Connect button in the upper right of the window to login before you can use the drive.

Once you are logged in, you should then be able to use the drive with Time Machine.

Ubuntu 19.10: File Sharing to Windows and Mac

Setting up Samba under Ubuntu 19.10 is relatively easy. This guide will show how to install Samba itself, then configure both a public drive meant to be shared among multiple users, and a per-user drive.

NOTE: This guide assumes your linux machine is on your local network.

First, install both samba and smbclient:

sudo apt install samba smbclient

Next, create a directory that will be the shared public drive, and set its ownership:

sudo mkdir -p /srv/samba/public
sudo chown nobody:nogroup /srv/samba/public
sudo chmod 777 /srv/samba/public

Now it’s time to configure Samba. There’s two basic things that need to be configured: setting the user security, and adding the public drive.

To set the user security, set security = user in the [global] section of /etc/samba/smb.conf.

Enable the per-user drive in /etc/samba/smb.conf:

    comment = Home Directories
    browseable = no
    read only = no

To add the public drive, add this section to the end of /etc/samba/smb.conf:

   comment = Public Files
   path = /srv/samba/public
   browsable = yes
   guest ok = yes
   read only = no
   create mask = 0755

Now, restart the Samba services to pick up these configuration changes:

sudo systemctl restart smbd.service nmbd.service

Since Samba doesn’t use the linux login credentials for a user, you must add each user that needs access to a shared drive using the smbpasswd command:

sudo smbpasswd -a <unix username>

Also, if you’re running a firewall on your linux machine, you’ll probably have to allow access for your local network. You can allow specific machines, or a subnet. I use ufw to control my firewall configuration, so for me I simply allowed all access for my internal network:

sudo ufw allow from

To connect to a drive from Windows, I right-click on the Network item in File Explorer and select Map network drive..., and use \\<hostname>\public or \\<hostname>\<unix username> as the Folder.

To connect to a drive from the Mac, I use Go -> Connect to Server... in the Finder, then use smb://<hostname>/public or smb://<hostname>/<unix username> as the address.