Yacman is a YAML configuration manager. It provides some convenience tools for dealing with YAML configuration files.

Please see this Python notebook for features and usage instructions and this document for API documentation.

Upgrading guide

How to upgrade to yacman v1.0.0. Yacman v1 provides 2 feature upgrades:

1. Constructors take the form of yacman.YAMLConfigManager.from_x(...) functions, to make it clearer how to create a new ym object.
2. It separates locks into read locks and write locks, to allow mutliple simultaneous readers.

Upgrading from v0.9.3 to v1.0.0

If you were using FutureYAMLConfigManager in v0.9.3, simply update your imports:

Change from:

from yacman import FutureYAMLConfigManager as YAMLConfigManager

to:

from yacman import YAMLConfigManager

2. Update any context managers to use write_lock or read_lock

from yacman import write_lock, read_lock

Change

with ym as locked_ym:
    locked_ym.write()

to

with write_lock(ym) as locked_ym:
    locked_ym.rebase_and_write()

Or, if you prefer to be more explicit:

with write_lock(ym) as locked_ym:
    locked_ym.rebase()
    locked_ym.write()

In the new system, you must use rebase() before write() if you want to allow for multiple processes to possibly have written the file since you read it in. The rebase_and_write() convenience method combines these two calls.

More examples:

from yacman import YAMLConfigManager
from yacman import read_lock, write_lock

data = {"my_list": [1,2,3], "my_int": 8, "my_str": "hello world!", "my_dict": {"nested_val": 15}}

ym = YAMLConfigManager(data)

ym["my_list"]
ym["my_int"]
ym["my_dict"]

# Use in a context manager to write to the file

ym["new_var"] = 15

# Use a write-lock, and rebase before writing to ensure you capture any changes since you loaded the file
with write_lock(ym) as locked_ym:
    locked_ym.rebase_and_write()

# Or, if you want to do it explicitly:
with write_lock(ym) as locked_ym:
    locked_ym.rebase()
    locked_ym.write()


# use a read lock to rebase -- this will replay any in-memory updates on top of whatever is re-read from the file
with read_lock(ym) as locked_ym:
    locked_ym.rebase()

# use a read lock to reset the in-memory object to whatever is on disk
with read_lock(ym) as locked_ym:
    locked_ym.reset()

Locking caveats

The write_lock() and read_lock() context managers use file-based locking that is NOT re-entrant. A process cannot acquire the same lock twice - it will deadlock waiting for itself. Do not nest lock contexts on the same file:

# WRONG - will deadlock:
with write_lock(cfg):
    some_function(cfg)

def some_function(cfg):
    with write_lock(cfg):  # Deadlock! Caller already holds this lock
        cfg.write()

# RIGHT - lock once at the top level:
with write_lock(cfg):
    some_function(cfg)

def some_function(cfg):
    cfg.write()  # No lock here - caller already holds it

If a function needs to write to a config file, either:

1. Have the caller acquire the lock and pass the already-locked object, OR
2. Have the function acquire the lock itself (document this in the function's docstring)

But never both.

3. Update any constructors to use the from_{x} functions

You can no longer just create a YAMLConfigManager object directly; now you need to use the constructor helpers.

Examples:

from yacman import YAMLConfigManager

data = {"my_list": [1,2,3], "my_int": 8, "my_str": "hello world!", "my_dict": {"nested_val": 15}}
file_path = "tests/data/full.yaml"
yaml_data = "myvar: myval"

yacman.YAMLConfigManager.from_yaml_file(file_path)
yacman.YAMLConfigManager.from_yaml_data(yaml_data)
yacman.YAMLConfigManager.from_obj(data)

In the past, you could load from a file and overwrite some attributes with a dict of variables, all from the constructor. Now it would is more explicit:

ym = yacman.YacMan.from_yaml_file(file_path)
ym.update_from_obj(data)

To exppand environment variables in values, use .exp.

ym.exp["text_expand_home_dir"]

From v0.9.3 (using future) to v1.X.X:

Switch back to:

from yacman import YAMLConfigManager

Demos

Some interactive demos

from yacman import YAMLConfigManager
ym = yacman.YAMLConfigManager(entries=["a", "b", "c"])
ym.to_dict()
ym

print(ym.to_yaml())

ym = YAMLConfigManager(entries={"top": {"bottom": ["a", "b"], "bottom2": "a"}, "b": "c"})
ym
print(ym.to_yaml())

ym = YAMLConfigManager(filepath="tests/data/conf_schema.yaml")
print(ym.to_yaml())
ym

ym = YAMLConfigManager(filepath="tests/data/empty.yaml")
print(ym.to_yaml())

ym = YAMLConfigManager(filepath="tests/data/list.yaml")
print(ym.to_yaml())

ym = YAMLConfigManager(YAMLConfigManager(filepath="tests/data/full.yaml").exp)
print(ym.to_yaml())

ym = YAMLConfigManager(filepath="tests/data/full.yaml")
print(ym.to_yaml(expand=True))