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Sorting HOW TO¶ Author. Andrew Dalke and Raymond Hettinger. Python lists have a built-in list.sort method that modifies the list in-place. There is also a sorted built-in function that builds a new sorted list from an iterable. In this document, we explore the various techniques for sorting data using Python.


Universally Unique Lexicographically Sortable Identifier

Project description

.. image::
.. image::
.. image::
.. image::
What is this?
This is a port of the original JavaScript ULID_ implementation to Python.
A ULID is a *universally unique lexicographically sortable identifier*. It is
- 128-bit compatible with UUID
- 1.21e+24 unique ULIDs per millisecond
- Lexicographically sortable!
- Canonically encoded as a 26 character string, as opposed to the 36 character UUID
- Uses Crockford's base32 for better efficiency and readability (5 bits per character)
- Case insensitive
- No special characters (URL safe)
In general the structure of a ULID is as follows:
.. code-block:: txt
01AN4Z07BY 79KA1307SR9X4MV3
---------- ----------------
Timestamp Randomness
48bits 80bits
For more information have a look at the original specification_.
Basic Usage
.. code-block:: python
>>> from ulid import ULID
>>> ulid =
>>> ulid.str
>>> ulid.timestamp
>>> ulid.datetime
datetime.datetime(2017, 9, 20, 22, 18, 59, 153000)
.. code-block:: bash
$ pip install python-ulid
Other implementations
- `ahawker/ulid <>`_
- `valohai/ulid2 <>`_
- `mdipierro/ulid <>`_
.. _ULID:
.. _specification:

Python3 Ulid Keeps Generating The Same Key In Excel

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Extracting text from a file is a common task in scripting and programming, and Python makes it easy. In this guide, we'll discuss some simple ways to extract text from a file using the Python 3 programming language.

Make sure you're using Python 3

In this guide, we'll be using Python version 3. Most systems come pre-installed with Python 2.7. While Python 2.7 is used in most legacy code, Python 3 is the present and future of the Python language. Unless you have a specific reason to write or support legacy Python code, we recommend working in Python 3.

For Microsoft Windows, Python 3 can be downloaded from the Python official website. When installing, make sure the 'Install launcher for all users' and 'Add Python to PATH' options are both checked, as shown in the image below.

On Linux, you can install Python 3 with your package manager. For instance, on Debian or Ubuntu, you can install it with the following command:

For macOS, the Python 3 installer can be downloaded from, as linked above. If you are using the Homebrew package manager, it can also be installed by opening a terminal window (ApplicationsUtilities), and running this command:

Running Python

On Linux and macOS, the command to run the Python 3 interpreter is python3. On Windows, if you installed the launcher, the command is py. The commands on this page use python3; if you're on Windows, substitute py for python3 in all commands.

Running Python with no options starts the interactive interpreter. For more information about using the interpreter, see Python overview: using the Python interpreter. If you accidentally enter the interpreter, you can exit it using the command exit() or quit().

Running Python with a file name will interpret that python program. For instance:

...runs the program contained in the file

Okay, how can we use Python to extract text from a text file?

Reading data from a text file

First, let's read a text file. Let's say we're working with a file named lorem.txt, which contains a few lines of Latin:


In all the examples that follow, we work with text contained in this file. Feel free to copy and paste the latin text above into a text file, and save it as lorem.txt, so that you can run the example code using this file as input.

A Python program can read a text file using the built-in open() function. For example, below is a Python 3 program that opens lorem.txt for reading in text mode, reads the contents into a string variable named contents, closes the file, and then prints the data.

Here, myfile is the name we give to our file object.

The 'rt' parameter in the open() function means 'we're opening this file to read text data'

The hash mark ('#') means that everything on the rest of that line is a comment, and it is ignored by the Python interpreter.

If you save this program in a file called, you can run it with the following command.

The command above outputs the contents of lorem.txt:

Using 'with open'

It's important to close your open files as soon as possible: open the file, perform your operation, and close it. Don't leave it open for extended periods of time.

When you're working with files, it's good practice to use the with compound statement. It's the cleanest way to open a file, operate on it, and close the file, all in one easy-to-read block of code. The file is automatically closed when the code block completes.

Using with, we can rewrite our program to look like this:


Indentation is important in Python. Python programs use white space at the beginning of a line to define scope, such as a block of code. We recommend you use four spaces per level of indentation, and that you use spaces rather than tabs. In the following examples, make sure your code is indented exactly as it's presented here.


Save the program as and execute it:


Reading text files line-by-line

In the examples so far, we've been reading in the whole file at once. Reading a full file is no big deal with small files, but generally speaking, it's not a great idea. For one thing, if your file is bigger than the amount of available memory, you'll encounter an error.

Python3 ulid keeps generating the same key lock

In almost every case, it's a better idea to read a text file one line at a time.

In Python, the file object is an iterator. An iterator is a type of Python object which behaves in certain ways when operated on repeatedly. For instance, you can use a for loop to operate on a file object repeatedly, and each time the same operation is performed, you'll receive a different, or 'next,' result.


For text files, the file object iterates one line of text at a time. It considers one line of text a 'unit' of data, so we can use a loop statement to iterate on the data one line at a time:


Notice that we're getting an extra line break ('newline') after every line. That's because two newlines are being printed. The first one is the newline at the end of every line of our text file. The second newline happens because, by default, print() adds a linebreak of its own at the end of whatever you've asked it to print.

Let's store our lines of text in a variable — specifically, a list variable — so we can look at it more closely.

Storing text data in a list variable

In Python, lists are similar to, but not the same as, an array in C or Java. A Python list contains indexed data, of varying lengths and types.


The output of this program is a little different. Instead of printing the contents of the list, this program prints our list object, which looks like this:


Here, we see the raw contents of the list. In its raw object form, a list is represented as a comma-delimited list. Here, each element is represented as a string, and each newline is represented as its escape character sequence, n.

Much like an array in C or Java, we can access the elements of a list by specifying an index number after the variable name, in brackets. Index numbers start at zero — other words, the nth element of a list has the numeric index n-1.


If you're wondering why the index numbers start at zero instead of one, you're not alone. Computer scientists have debated the usefulness of zero-based numbering systems in the past. In 1982, Edsger Dijkstra gave his opinion on the subject, explaining why zero-based numbering is the best way to index data in computer science. You can read the memo yourself — he makes a compelling argument.


We can print the first element of lines by specifying index number 0, contained in brackets after the name of the list:



Or the third line, by specifying index number 2:


But if we try to access an index for which there is no value, we get an error:




A list object is an iterator, so to print every element of the list, we can iterate over it with


But we're still getting extra newlines. Each line of our text file ends in a newline character ('n'), which is being printed. Also, after printing each line, print() adds a newline of its own, unless you tell it to do otherwise.

We can change this default behavior by specifying an endparameter in our print() call:

By setting end to an empty string (represented as two single quotes, with no space between), we tell print() to print nothing at the end of a line, instead of a newline character.


Our revised program looks like this:


The newlines you see here are actually in the file; they're a special character ('n') at the end of each line. We want to get rid of these, so we don't have to worry about them while we process the file.

How to strip newlines

To remove the newlines completely, we can strip them. To strip a string is to remove one or more characters, usually whitespace, from either the beginning or end of the string.


This process is sometimes also called 'trimming.'

Python 3 string objects have a method called rstrip(), which strips characters from the right side of a string. The English language reads left-to-right, so stripping from the right side removes characters from the end.

If the variable is named mystring, we can strip its right side with mystring.rstrip(chars), where chars is a string of characters to strip. For example, '123abc'.rstrip('bc') returns 123a.


When you represent a string in your program with its literal contents, it's called a string literal. In Python (as in most programming languages), string literals are always quoted — enclosed on either side by single (') or double (') quotes. In Python, single and double quotes are equivalent; you can use one or the other, as long as they match on both ends of the string. It's traditional to represent a human-readable string (such as Hello) in double-quotes ('Hello'). If you're representing a single character (such as b), or a single special character such as the newline character (), it's traditional to use single quotes ('b', '). For more information about how to use strings in Python, you can read the documentation of strings in Python.

The statement string.rstrip('n') will strip a newline character from the right side of string. The following version of our program strips the newlines when each line is read from the text file:

The text is now stored in a list variable, so individual lines can be accessed by index number. Newlines were stripped, so we don't have to worry about them. We can always put them back later if we reconstruct the file and write it to disk.

Now, let's search the lines in the list for a specific substring.

Searching text for a substring

Let's say we want to locate every occurrence of a certain phrase, or even a single letter. For instance, maybe we need to know where every 'e' is. We can accomplish this using the string's find() method.

The list stores each line of our text as a string object. All string objects have a method, find(), which locates the first occurrence of a substrings in the string.

Let's use the find() method to search for the letter 'e' in the first line of our text file, which is stored in the list mylines. The first element of mylines is a string object containing the first line of the text file. This string object has a find() method.

In the parentheses of find(), we specify parameters. The first and only required parameter is the string to search for, 'e'. The statement mylines[0].find('e') tells the interpreter to search forward, starting at the beginning of the string, one character at a time, until it finds the letter 'e.' When it finds one, it stops searching, and returns the index number where that 'e' is located. If it reaches the end of the string, it returns -1 to indicate nothing was found.




The return value '3' tells us that the letter 'e' is the fourth character, the 'e' in 'Lorem'. (Remember, the index is zero-based: index 0 is the first character, 1 is the second, etc.)

The find() method takes two optional, additional parameters: a start index and a stop index, indicating where in the string the search should begin and end. For instance, string.find('abc', 10, 20) will search for the substring 'abc', but only from the 11th to the 21st character. If stop is not specified, find() starts at index start, and stops at the end of the string.


For instance, the following statement searchs for 'e' in mylines[0], beginning at the fifth character.


In other words, starting at the 5th character in line[0], the first 'e' is located at index 24 (the 'e' in 'nec').


To start searching at index 10, and stop at index 30:


(The first 'e' in 'Maecenas').


If find() doesn't locate the substring in the search range, it returns the number -1, indicating failure:




There were no 'e' occurrences between indices 25 and 30.

Finding all occurrences of a substring

But what if we want to locate every occurrence of a substring, not just the first one we encounter? We can iterate over the string, starting from the index of the previous match.

In this example, we'll use a while loop to repeatedly find the letter 'e'. When an occurrence is found, we call find again, starting from a new location in the string. Specifically, the location of the last occurrence, plus the length of the string (so we can move forward past the last one). When find returns -1, or the start index exceeds the length of the string, we stop.



Incorporating regular expressions

For complex searches, use regular expressions.

The Python regular expressions module is called re. To use it in your program, import the module before you use it:

The re module implements regular expressions by compiling a search pattern into a pattern object. Methods of this object can then be used to perform match operations.

For example, let's say you want to search for any word in your document which starts with the letter d and ends in the letter r. We can accomplish this using the regular expression 'bdw*rb'. What does this mean?

character sequencemeaning
bA word boundary matches an empty string (anything, including nothing at all), but only if it appears before or after a non-word character. 'Word characters' are the digits 0 through 9, the lowercase and uppercase letters, or an underscore ('_').
dLowercase letter d.
w*w represents any word character, and * is a quantifier meaning 'zero or more of the previous character.' So w* will match zero or more word characters.
rLowercase letter r.
bWord boundary.

So this regular expression will match any string that can be described as 'a word boundary, then a lowercase 'd', then zero or more word characters, then a lowercase 'r', then a word boundary.' Strings described this way include the words destroyer, dour, and doctor, and the abbreviation dr.

To use this regular expression in Python search operations, we first compile it into a pattern object. For instance, the following Python statement creates a pattern object named pattern which we can use to perform searches using that regular expression.


The letter r before our string in the statement above is important. It tells Python to interpret our string as a raw string, exactly as we've typed it. If we didn't prefix the string with an r, Python would interpret the escape sequences such as b in other ways. Whenever you need Python to interpret your strings literally, specify it as a raw string by prefixing it with r.

Now we can use the pattern object's methods, such as search(), to search a string for the compiled regular expression, looking for a match. If it finds one, it returns a special result called a match object. Otherwise, it returns None, a built-in Python constant that is used like the boolean value 'false'.




To perform a case-insensitive search, you can specify the special constant re.IGNORECASE in the compile step:


Putting it all together

So now we know how to open a file, read the lines into a list, and locate a substring in any given element of that list. Let's use this knowledge to build some example programs.

Print all lines containing substring

The program below reads a log file line by line. If the line contains the word 'error,' it is added to a list called errors. If not, it is ignored. The lower() string method converts all strings to lowercase for comparison purposes, making the search case-insensitive without altering the original strings.

Note that the find() method is called directly on the result of the lower() method; this is called method chaining. Also, note that in the print() statement, we construct an output string by joining several strings with the + operator.


Example input (text file logfile.txt)

Example output

Extract all lines containing substring, using regex

The program below is similar to the above program, but using the re regular expressions module. The errors and line numbers are stored as tuples, e.g., (linenum, line). The tuple is created by the additional enclosing parentheses in the errors.append() statement. The elements of the tuple are referenced similar to a list, with a zero-based index in brackets. As constructed here, err[0] is a linenum and err[1] is the associated line containing an error.


Output (same as above)

Extract all lines containing a phone number

The program below prints any line of a text file, info.txt, which contains a US or international phone number. It accomplishes this with the regular expression '(+d{1,2})?[s.-]?d{3}[s.-]?d{4}'. This regex matches the following phone number notations:

  • 123-456-7890
  • (123) 456-7890
  • 123 456 7890
  • 123.456.7890
  • +91 (123) 456-7890


Search a dictionary for words

The program below searches the dictionary for any words that start with h and end in pe. For input, it uses a dictionary file included on many Unix systems, /usr/share/dict/words.


Additional information

  • See our Python definition for additional help and information.
  • For more information about regular expressions, see our regular expressions quick reference.
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