Last time we started a new series of articles about analogies in Python and JavaScript. We had a look at lists, arrays, dictionaries, objects, and strings, conditional assignments, and parsing integers. This time we will go through more interesting and more complex things like serializing dictionaries and lists to JSON, operations with regular expressions, as well as raising and catching errors.
JSON
When working with APIs it is very usual to serialize objects to JSON format and be able to parse JSON strings.
In Python it is done with the json module like this:
import json
json_data = json.dumps(dictionary, indent=4)
dictionary = json.loads(json_data)Here we'll indent the nested elements in the JSON string by 4 spaces.
In JavaScript there is a JSON object that has methods to create and parse JSON strings:
json_data = JSON.stringify(dictionary, null, 4);
dictionary = JSON.parse(json_data);Splitting strings by regular expressions
Regular expressions are multi-tool that once you master, you can accomplish lots of things.
In the last article, we saw how one can join lists of strings into a single string. But how can you split a long string into lists of strings? What if the delimiter can be not a single character as the comma, but a range of possible variations? This can be done with regular expressions and the split() method.
In Python, the split() method belongs to the regular expression pattern object. This is how you could split a text string into sentences by punctuation marks:
import re
# One or more characters of "!?." followed by whitespace
delimiter = re.compile(r'[!?\.]+\s*')
text = "Hello!!! What's new? Follow me."
sentences = delimiter.split(text)
# sentences == ['Hello', "What's new", 'Follow me', '']In JavaScript the split() method belongs to the string:
// One or more characters of "!?." followed by whitespace
delimiter = /[!?\.]+\s*/;
text = "Hello!!! What's new? Follow me.";
sentences = text.split(delimiter)
// sentences === ["Hello", "What's new", "Follow me", ""]Matching regular expression patterns in strings
Regular expressions are often used to validate data from the forms.
For example, to validate if the entered email address is correct, you would need to match it against a regular expression pattern. In Python that would look like this:
import re
# name, "@", and domain
pattern = re.compile(r'([\w.+\-]+)@([\w\-]+\.[\w\-.]+)')
match = pattern.match('hi@example.com')
# match.group(0) == 'hi@example.com'
# match.group(1) == 'hi'
# match.group(2) == 'example.com'If the text matches the pattern, it returns a match object with the group() method to read the whole matched string, or separate captures of the pattern that were defined with the parenthesis. 0 means getting the whole string, 1 means getting the match in the first group, 2 means getting the match in the second group, and so on. If the text doesn't match the pattern, the None value will be returned.
In JavaScript the match() method belongs to the string and it returns either a match object, or null. Pretty similar:
// name, "@", and domain
pattern = /([\w.+\-]+)@([\w\-]+\.[\w\-.]+)/;
match = 'hi@example.com'.match(pattern);
// match[0] === 'hi@example.com'
// match[1] === 'hi'
// match[2] === 'example.com'The match object in JavaScript acts as an array. Its value at the zeroth position is the whole matched string. The other indexes correspond to the captures of the pattern defined with the parenthesis.
Moreover, sometimes you need to search if a specific value exists in a string and at which letter position it will be found. That can be done with the search() method.
In Python this method belongs to the regular expression pattern and it returns the match object. The match object has the start() method telling at which letter position the match starts:
text = 'Say hi at hi@example.com'
first_match = pattern.search(text)
if first_match:
start = first_match.start() # start == 10In JavaScript the search() method belongs to the string and it returns just an integer telling at which letter position the match starts. If nothing is found, -1 is returned:
text = 'Say hi at hi@example.com';
first_match = text.search(pattern);
if (first_match > -1) {
start = first_match; // start === 10
}
Replacing patterns in strings using regular expressions
Replacing with regular expressions usually happen when cleaning up data, or adding additional features. For example, we could take some text and make all email addresses clickable.
Python developers would use the sub() method of the regular expression pattern:
html = pattern.sub(
r'<a href="mailto:\g<0>">\g<0></a>',
'Say hi at hi@example.com',
)
# html == 'Say hi at <a href="mailto:hi@example.com">hi@example.com</a>'JavaScript developers would use the replace() method of the string:
html = 'Say hi at hi@example.com'.replace(
pattern,
'<a href="mailto:$&">$&</a>',
);
// html === 'Say hi at <a href="mailto:hi@example.com">hi@example.com</a>'In Python the captures, also called as "backreferences", are accessible in the replacement string as \g<0>, \g<1>, \g<2>, etc. In JavaScript the same is accessible as $&, $1, $2, etc. Backreferences are usually used to wrap some strings or to switch places of different pieces of text.
It is also possible to replace a match with a function call. This can be used to do replacements within replacements or to count or collect some features of a text. For example, using replacements with function calls in JavaScript, I once wrote a fully functional HTML syntax highlighter.
Here let's change all email addresses in a text to UPPERCASE.
In Python, the replacement function receives the match object. We can use its group() method to do something with the matched text and return a text as a replacement:
text = pattern.sub(
lambda match: match.group(0).upper(),
'Say hi at hi@example.com',
)
# text == 'Say hi at HI@EXAMPLE.COM'In JavaScript the replacement function receives the whole match string, the first capture, the second capture, etc. We can do what we need with those values and then return some string as a replacement:
text = 'Say hi at hi@example.com'.replace(
pattern,
function(match, p1, p2) {
return match.toUpperCase();
}
);
// text === 'Say hi at HI@EXAMPLE.COM'Error handling
Contrary to Python, client-side JavaScript normally isn't used for saving or reading files or connecting to remote databases. So try..catch blocks are quite rare in JavaScript compared to try..except analogy in Python.
Anyway, error handling can be used with custom user errors implemented and raised in JavaScript libraries and caught in the main code.
The following example in Python shows how to define a custom exception class MyException, how to raise it in a function, and how to catch it and handle in a try..except..finally block:
class MyException(Exception):
def __init__(self, message):
self.message = message
def __str__(self):
return self.message
def proceed():
raise MyException('Error happened!')
try:
proceed()
except MyException as err:
print('Sorry! {}'.format(err))
finally:
print('Finishing') The following example in JavaScript does exactly the same: here we define a MyException class, throw it in a function, and catch it and handle in the try..catch..finally block.
function MyException(message) {
this.message = message;
this.toString = function() {
return this.message;
}
}
function proceed() {
throw new MyException('Error happened!');
}
try {
proceed();
} catch (err) {
if (err instanceof MyException) {
console.log('Sorry! ' + err);
}
} finally {
console.log('Finishing');
}
The MyException class in both languages has a parameter message and a method to represent itself as a string using the value of the message.
Of course, exceptions should be raised/thrown just in the case of errors. And you define what is an error in your module design.
The Takeaways
- Serialization to JSON is quite straightforward in both, Python and JavaScript.
- Regular expressions can be used as multi-tools when working with textual data.
- You can do replacements with function calls in both languages.
- For more sophisticated software design you can use custom error classes.
As I mentioned last time, you can grab a side-by-side comparison of Python and JavaScript that I compiled for you (and my future self). Side by side you will see features from traditional list, array, dictionary, object, and string handling to modern string interpolation, lambdas, generators, sets, classes, and everything else. Use it for good.
In the next part of the series, we will have a look at textual templates, list unpacking, lambda functions, iteration without indexes, generators, and sets. Stay tuned!
Cover photo by Benjamin Hung.
No comments:
Post a Comment