yacman 0.9.3

A standardized configuration object for reference genome assemblies

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.

The v0.9.3 transition release would has versions, really:

• attmap-based version (YacAttMap)
• non-attmap-but-mostly-compatible (YAMLConfigManager)
• new future object (FutureYAMLConfigManager...), which is not-backwards-compatible.

In v1.0.0, FutureYAMLConfigManager will be renamed to YAMLConfigManager and the old stuff will be removed. Here's how to transition your code:

Use the FutureYAMLConfigManager in 0.9.3

1. Import the FutureYAMLConfigManager

Change from:

from yacman import YAMLConfigManager

to

from yacman import FutureYAMLConfigManager as YAMLConfigManager

Once we switch from v0.9.3 to v1.X.X, you will need to switch back.

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.write()

More examples:

from yacman import FutureYAMLConfigManager as YAMLConfigManager


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

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

with read(ym) as locked_ym:
	locked_ym.rebase()

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 FutureYAMLConfigManager as 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 FutureYAMLConfigManager as 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))