pkl

Evaluate the given Pkl modules and produce their rendering results

$ pkl eval [module.pkl]

$ pkl server

$ pkl test [module.pkl]

$ pkl repl

$ pkl project package [path/to/project_directory]

$ pkl project resolve [path/to/project_directory]

Since there is no direct 'pkl' command, interaction with .pkl files is handled through Python scripts or the Python interpreter.

Conceptual Python Interaction (Loading a file):
python [options] your_script.py [script_arguments]

Where your_script.py contains code such as:
import pickle
with open('your_file.pkl', 'rb') as f:
data = pickle.load(f)
print(data)

Or directly from the command line for a quick view (though often not fully representative of complex objects):
python -c "import pickle; with open('your_file.pkl', 'rb') as f: obj = pickle.load(f); print(obj)"

N/A
    There is no direct 'pkl' command with command-line parameters. Interaction with .pkl files is typically done programmatically using Python's pickle module, where functions like pickle.load() and pickle.dump() accept various arguments for controlling the serialization process.

While not a standalone Linux command, .pkl refers to files created using Python's pickle module. These files store Python objects in a serialized (byte stream) format, allowing them to be saved to disk and loaded back into a Python program later. This process is called pickling (serialization) and unpickling (deserialization).

The primary purpose of .pkl files is to preserve the state of Python objects, making them useful for tasks like machine learning model persistence, caching data structures, or transferring complex Python objects between different Python environments. Unlike human-readable formats like JSON or XML, .pkl files are binary and Python-specific, meaning they cannot be easily inspected or modified without a Python interpreter.

Interaction with .pkl files is exclusively performed programmatically using Python scripts that import the pickle module.

Security Risk: Deserializing a .pkl file from an untrusted source is extremely dangerous. The pickle module is not secure. It is possible to construct malicious pickle data which will execute arbitrary code upon unpickling. Never unpickle data received from an untrusted or unauthenticated source.

Python Version Compatibility: Pickle files can sometimes be incompatible between different Python versions. While the pickle protocol has evolved, older Python versions may not be able to unpickle files created by newer versions, and vice-versa, especially when using specific protocol versions.

Not Human-Readable: .pkl files are binary and not designed for human inspection. Debugging issues or understanding the content without Python code can be challenging.

To save a Python object to a .pkl file, you use pickle.dump():
import pickle

my_object = {'name': 'Alice', 'age': 30, 'city': 'New York'}

with open('my_data.pkl', 'wb') as f: # 'wb' for write binary
pickle.dump(my_object, f)

To load an object from a .pkl file, you use pickle.load():
import pickle

with open('my_data.pkl', 'rb') as f: # 'rb' for read binary
loaded_object = pickle.load(f)

print(loaded_object)

The pickle module supports several protocol versions. By default, it uses the highest available protocol. You can specify a protocol version when dumping:
import pickle

my_object = [1, 2, 3]

with open('my_data_protocol2.pkl', 'wb') as f:
pickle.dump(my_object, f, protocol=2) # Use protocol 2 for compatibility
Using older protocols can improve compatibility with older Python versions but may come at the cost of larger file sizes or reduced performance.

The pickle module has been a fundamental part of the Python standard library since its early versions, providing a native mechanism for object serialization. Over time, different 'protocol' versions have been introduced to improve performance, reduce file size, and handle new Python features. For instance, protocol 0 was the original text-based format, while later protocols (e.g., 2, 3, 4, 5) introduced binary formats and optimizations. Its development is tied directly to the evolution of the Python language itself and its need for robust object persistence.

python(1), json(1), gzip(1), tar(1)