Metadata-Version: 2.4
Name: yacman
Version: 0.9.5
Summary: A standardized configuration object for reference genome assemblies
Home-page: https://github.com/databio/yacman
Author: Nathan Sheffield, Michal Stolarczyk
Author-email: nathan@code.databio.org
License: BSD2
Keywords: bioinformatics,sequencing,ngs
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: attmap>=0.13.0
Requires-Dist: jsonschema>=3.2.0
Requires-Dist: oyaml
Requires-Dist: pyyaml>=3.13
Requires-Dist: ubiquerg>=0.7.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
Dynamic: requires-dist
Dynamic: summary

<img src="https://raw.githubusercontent.com/databio/yacman/master/docs/img/yacman_logo.svg?sanitize=true" alt="yacman" height="70"/><br>
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Yacman is a YAML configuration manager. It provides some convenience tools for dealing with YAML configuration files.

Please see [this](docs/usage.md) Python notebook for features and usage instructions and [this](docs/api_docs.md) 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 has 3 versions of the basic yacman object, namely: 
- attmap-based version (YacAttMap)
- non-attmap-but-mostly-compatible (YAMLConfigManager)
- new future object (FutureYAMLConfigManager...), which is explicitly not backwards compatible with the attmap version.

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:

```python
from yacman import YAMLConfigManager
```

to 

```python
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`

```python
from yacman import write_lock, read_lock
```

Change

```python
with ym as locked_ym:
    locked_ym.write()
```	

to


```python
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.



More examples:

```python

from yacman import FutureYAMLConfigManager as 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(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()

```




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:

```python
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:

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

To exppand environment variables in values, use `.exp`.

```python
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

```python
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))

```
