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What's New

This release contains a minor change to the startup script, which is typically located in ~/.config/marcel/startup.py. Previously, you could include marcel commands to be run in the startup process (just before the first prompt), by assigning a string containing marcel commands to RUN_ON_STARTUP.

As of this release, RUN_ON_STARTUP processing is no longer supported. Instead, pass the script to the run_on_startup function. You can call run_on_startup multiple times in your startup script. The scripts are not run immediately, but will be run in the order provided before the first prompt appears.

Marcel

Marcel is a shell. The main idea is to rely on piping as the primary means of composition, as with any Unix or Linux shell. However, instead of passing strings from one command to the next, marcel passes Python values: builtin types such as lists, tuples, strings, and numbers; but also objects representing files and processes.

Linux has extremely powerful commands such as awk and find. Most people know how to do a few simple operations using these commands. But it is not easy to exploit the full power of these commands due to their reliance on extensive "sublanguages" which do:

  • Filtering: What data is of interest?
  • Processing: What should be done with the data?
  • Formatting: How should results be presented?

By contrast, marcel has no sublanguages. You use marcel operators combined with Python code to filter data, process it, and control command output.

The commands and syntax supported by a shell constitute a language which can be used to create scripts. Of course, in creating a script, you rely on language features that you typically do not use interactively: control structures, data types, and abstraction mechanisms (e.g. functions), for example. Viewed as a programming language, shell scripting languages are notoriously bad. I didn't think it was wise to bring another one into the world. So marcel takes a different approach, using Python as a scripting language, (see below for more on scripting).

Pipelines

Marcel provides commands, called operators, which do the basic work of a shell. An operator takes a stream of data as input, and generates another stream as output. Operators can be combined by pipes, causing one operator's output to be the next operator's input. For example, this command uses the ls and map operators to list the names and sizes of files in the /home/jao directory:

ls /home/jao | map (lambda f: (f, f.size))
  • The ls operator produces a stream of File objects, representing the contents of the /home/jao directory.
  • | is the symbol denoting a pipe, as in any Linux shell.
  • The pipe connects the output stream from ls to the input stream of the next operator, map.
  • The map operator applies a given function to each element of the input stream, and writes the output from the function to the output stream. The function is enclosed in parentheses. It is an ordinary Python function, except that the keyword lambda is optional. In this case, an incoming File is mapped to a tuple containing the file and the file's size.

A pipeline is a sequence of operators connected by pipes. They can be used directly on the command line, as above. They also have various other uses in marcel. For example, a pipeline can be assigned to a variable, essentially defining a new operator. For example, here is a pipeline, assigned to the variable recent, which selects Files modified within the past day:

recent = (| select (file: now() - file.mtime < days(1)) |) 
  • The pipeline being defined is bracketed by (|...|). (Without the brackets, marcel would attempt to evaluate the pipeline immediately, and then complain because the parameter file is not bound.)
  • The pipeline contains a single operator, select, which uses a function to define the items of interest. In this case, select operates on a File, bound to the parameter file.
  • now() is a function defined by marcel which gives the current time in seconds since the epoch, (i.e., it is just time.time()).
  • File objects have an mtime property, providing the time since the last content modification.
  • days() is another function defined by marcel, which simply maps days to seconds, i.e., it multiplies by 24 * 60 * 60.

This pipeline can be used in conjunction with any pipeline yielding files. E.g., to locate the recently changed files in ~/git/myproject:

ls ~/git/myproject | recent

Functions

As shown above, a number of operators, like map and select, take Python functions as command-line arguments. Functions can also be invoked to obtain the value of an environment variable. For example, to list the contents of your home directory, you could write:

ls /home/(USER)

This concatenates the string /home/ with the string resulting from the evaluation of the expression lambda: USER. USER is a marcel environment variable identifying the current user, (so this command is equivalent to ls ~).

If you simply want to evaluate a Python expression, you could use the map operator, e.g.

map (5 + 6)

which prints 11. Marcel permits the map operator to be inferred, so this also works:

(5 + 6)

In general, you can elide map from any pipeline.

Executables

In addition to using built-in operators, you can, of course, call any executable. Pipelines may contain a mixture of marcel operators and host executables. Piping between operators and executables is done via streams of strings.

For example, this command combines operators and executables. It scans /etc/passwd and lists the usernames of users whose shell is /bin/bash. cat, xargs, and echo are Linux executables. map and select are marcel operators. The output is condensed into one line through the use of xargs and echo.

cat /etc/passwd \
| map (line: line.split(':')) \
| select (*line: line[-1] == '/bin/bash') \
| map (user, *_: user) \
| xargs echo
  • cat /etc/passwd: Obtain the contents of the file. Lines are piped to subsequent commands.
  • map (line: line.split(':')): Split the lines at the : separators, yielding 7-tuples.
  • select (*line: line[-1] == '/bin/bash'): select those lines in which the last field is /bin/bash.
  • map (user, *_: user) |: Keep the username field of each input tuple.
  • xargs echo: Combine the incoming usernames into a single line, which is printed to stdout.

Shell Features

Marcel provides:

  • Command history: A history operator, rerunning and editing of previous commands, reverse search, etc.
  • Customizable prompts: Configured in Python, of course.
  • Tab completion: For operators, flags, and filename arguments.
  • Help: Extensive help facility, providing information on concepts, objects, and operators.
  • Customizable color highlighting: The colors used to render output for builtin types such as File and Process, and help output can be customized too.
  • Dynamic reconfiguration: Changes to configuration and startup scripts are picked up without restarting.

Scripting

Marcel's syntax for constructing and running pipelines, and defining and using variables and functions, was designed for interactive usage. Instead of extending this syntax to a full-fledged scripting language, marcel provides a Python API, allowing Python to be used as the scripting language. While Python is sometimes considered to already be a scripting language, it isn't really. Executing shell commands from Python code is cumbersome. You've got to use os.system, or subprocess.Popen, and write some additional code to do the integration.

Marcel provides a Python module, marcel.api, which brings shell commands into Python in a much cleaner way. For example, to list file names and sizes in /home/jao:

from marcel.api import *

for file, size in ls('/home/jao') | map(lambda f: (f, f.size)):
    print(f'{file.name}: {size}') 

This code uses the ls and map functions, provided by marcel.api. These correspond to the marcel operators ls and map that you can use on the command line. Output from the ls is a stream of Files, which are piped to map, which maps files to (file, file size) tuples. ls ... | map ... defines a pipeline (just as on the command line). The Python class representing pipelines defines iter, so that the pipeline's output can be iterated over using the standard Python for loop.

Installation

To install marcel locally (i.e., available only to your username):

python3 -m pip install marcel

This command installs marcel for the current user. To install for the entire system, use sudo python3 -m pip install --prefix ... instead. (The value of the --prefix flag should be something like /usr/local.)

Marcel depends on dill. This package will be installed automatically if needed, when marcel is installed via pip.