Reputation: 28644
How can I parse a YAML file in Python
How can I parse a YAML file in Python?
Upvotes: 1142
Views: 1506015
Answers (11)
Reputation: 3270
IO is simpler with dummio, a package I created. Just pip install dummio. Then
import dummio
# read
data = dummio.yaml.load(filepath)
# write
dummio.yaml.save(data, filepath=filepath)
Note that this works even if filepath is a cloud path (s3, gcs, azure). The package supports many other data types and file formats, not only dict/yaml.
Upvotes: 0
Reputation: 76802
If you have YAML that conforms to the YAML 1.2 specification (released 2009) then you should use ruamel.yaml (disclaimer: I am the author of that package). It is essentially a superset of PyYAML, which supports most of YAML 1.1 (from 2005).
If you want to be able to preserve your comments when round-tripping, you certainly should use ruamel.yaml.
Upgrading @Jon's example is easy:
import ruamel.yaml as yaml
with open("example.yaml") as stream:
try:
print(yaml.safe_load(stream))
except yaml.YAMLError as exc:
print(exc)
Use safe_load() unless you really have full control over the input, need it (seldom the case) and know what you are doing.
If you are using pathlib Path for manipulating files, you are better of using the new API ruamel.yaml provides:
from ruamel.yaml import YAML
from pathlib import Path
path = Path('example.yaml')
yaml = YAML(typ='safe')
data = yaml.load(path)
Upvotes: 91
Reputation: 21149
Example:
defaults.yaml
url: https://www.google.com
environment.py
from ruamel import yaml
data = yaml.safe_load(open('defaults.yaml'))
data['url']
Upvotes: 13
Reputation: 63724
The easiest and purest method without relying on C headers is PyYaml (documentation), which can be installed via pip install pyyaml:
import yaml
with open("example.yaml") as stream:
try:
print(yaml.safe_load(stream))
except yaml.YAMLError as exc:
print(exc)
And that's it. A plain yaml.load() function also exists, but yaml.safe_load() should always be preferred to avoid introducing the possibility for arbitrary code execution. So unless you explicitly need the arbitrary object serialization/deserialization use safe_load.
Note the PyYaml project supports versions up through the YAML 1.1 specification. If YAML 1.2 specification support is needed, see ruamel.yaml as noted in this answer.
Also, you could also use a drop in replacement for pyyaml, that keeps your yaml file ordered the same way you had it, called oyaml. View synk of oyaml here
Upvotes: 1490
Reputation: 14621
I would suggest to use the pyyaml library, together with the in-built pathlib library.
You will need to build a pathlib.Path object first:
from pathlib import Path
import yaml
path: Path = Path("/tmp/file.yaml")
# Make sure the path exists
assert path.exists()
# Read file and parse with pyyaml
dictionnaire = yaml.safe_load(path.read_text())
This works fine with modern versions of Python 3.
You do not need with use the open file method this way. The code is a slightly more concise and you can easily check if the file exists, before you actually try to parse the YAML file.
Upvotes: 3
Reputation: 136665
Read & Write YAML files with Python 2+3 (and unicode)
# -*- coding: utf-8 -*-
import yaml
import io
# Define data
data = {
'a list': [
1,
42,
3.141,
1337,
'help',
u'€'
],
'a string': 'bla',
'another dict': {
'foo': 'bar',
'key': 'value',
'the answer': 42
}
}
# Write YAML file
with io.open('data.yaml', 'w', encoding='utf8') as outfile:
yaml.dump(data, outfile, default_flow_style=False, allow_unicode=True)
# Read YAML file
with open("data.yaml", 'r') as stream:
data_loaded = yaml.safe_load(stream)
print(data == data_loaded)
Created YAML file
a list:
- 1
- 42
- 3.141
- 1337
- help
- €
a string: bla
another dict:
foo: bar
key: value
the answer: 42
Common file endings
.yml and .yaml
Alternatives
- CSV: Super simple format (read & write)
- JSON: Nice for writing human-readable data; VERY commonly used (read & write)
- YAML: YAML is a superset of JSON, but easier to read (read & write, comparison of JSON and YAML)
- pickle: A Python serialization format (read & write) ⚠️ Using pickle with files from 3rd parties poses an uncontrollable arbitrary code execution risk.
- MessagePack (Python package): More compact representation (read & write)
- HDF5 (Python package): Nice for matrices (read & write)
- XML: exists too *sigh* (read & write)
For your application, the following might be important:
- Support by other programming languages
- Reading / writing performance
- Compactness (file size)
See also: Comparison of data serialization formats
In case you are rather looking for a way to make configuration files, you might want to read my short article Configuration files in Python
Upvotes: 240
Reputation:
I made my own script for this. Feel free to use it, as long as you keep the attribution. The script can parse yaml from a file (function load), parse yaml from a string (function loads) and convert a dictionary into yaml (function dumps). It respects all variable types.
# © didlly AGPL-3.0 License - github.com/didlly
def is_float(string: str) -> bool:
try:
float(string)
return True
except ValueError:
return False
def is_integer(string: str) -> bool:
try:
int(string)
return True
except ValueError:
return False
def load(path: str) -> dict:
with open(path, "r") as yaml:
levels = []
data = {}
indentation_str = ""
for line in yaml.readlines():
if line.replace(line.lstrip(), "") != "" and indentation_str == "":
indentation_str = line.replace(line.lstrip(), "").rstrip("\n")
if line.strip() == "":
continue
elif line.rstrip()[-1] == ":":
key = line.strip()[:-1]
quoteless = (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
)
if len(line.replace(line.strip(), "")) // 2 < len(levels):
if quoteless:
levels[len(line.replace(line.strip(), "")) // 2] = f"[{key}]"
else:
levels[len(line.replace(line.strip(), "")) // 2] = f"['{key}']"
else:
if quoteless:
levels.append(f"[{line.strip()[:-1]}]")
else:
levels.append(f"['{line.strip()[:-1]}']")
if quoteless:
exec(
f"data{''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}]"
+ " = {}"
)
else:
exec(
f"data{''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}']"
+ " = {}"
)
continue
key = line.split(":")[0].strip()
value = ":".join(line.split(":")[1:]).strip()
if (
is_float(value)
or is_integer(value)
or value == "True"
or value == "False"
or ("[" in value and "]" in value)
):
if (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
):
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}] = {value}"
)
else:
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}'] = {value}"
)
else:
if (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
):
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}] = '{value}'"
)
else:
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}'] = '{value}'"
)
return data
def loads(yaml: str) -> dict:
levels = []
data = {}
indentation_str = ""
for line in yaml.split("\n"):
if line.replace(line.lstrip(), "") != "" and indentation_str == "":
indentation_str = line.replace(line.lstrip(), "")
if line.strip() == "":
continue
elif line.rstrip()[-1] == ":":
key = line.strip()[:-1]
quoteless = (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
)
if len(line.replace(line.strip(), "")) // 2 < len(levels):
if quoteless:
levels[len(line.replace(line.strip(), "")) // 2] = f"[{key}]"
else:
levels[len(line.replace(line.strip(), "")) // 2] = f"['{key}']"
else:
if quoteless:
levels.append(f"[{line.strip()[:-1]}]")
else:
levels.append(f"['{line.strip()[:-1]}']")
if quoteless:
exec(
f"data{''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}]"
+ " = {}"
)
else:
exec(
f"data{''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}']"
+ " = {}"
)
continue
key = line.split(":")[0].strip()
value = ":".join(line.split(":")[1:]).strip()
if (
is_float(value)
or is_integer(value)
or value == "True"
or value == "False"
or ("[" in value and "]" in value)
):
if (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
):
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}] = {value}"
)
else:
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}'] = {value}"
)
else:
if (
is_float(key)
or is_integer(key)
or key == "True"
or key == "False"
or ("[" in key and "]" in key)
):
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}[{key}] = '{value}'"
)
else:
exec(
f"data{'' if line == line.strip() else ''.join(str(i) for i in levels[:line.replace(line.lstrip(), '').count(indentation_str) if indentation_str != '' else 0])}['{key}'] = '{value}'"
)
return data
def dumps(yaml: dict, indent="") -> str:
"""A procedure which converts the dictionary passed to the procedure into it's yaml equivalent.
Args:
yaml (dict): The dictionary to be converted.
Returns:
data (str): The dictionary in yaml form.
"""
data = ""
for key in yaml.keys():
if type(yaml[key]) == dict:
data += f"\n{indent}{key}:\n"
data += dumps(yaml[key], f"{indent} ")
else:
data += f"{indent}{key}: {yaml[key]}\n"
return data
print(load("config.yml"))
Example
config.yml
level 0 value: 0
level 1:
level 1 value: 1
level 2:
level 2 value: 2
level 1 2:
level 1 2 value: 1 2
level 2 2:
level 2 2 value: 2 2
Output
{'level 0 value': 0, 'level 1': {'level 1 value': 1, 'level 2': {'level 2 value': 2}}, 'level 1 2': {'level 1 2 value': '1 2', 'level 2 2': {'level 2 2 value': 2 2}}}
Upvotes: 0
Reputation: 5219
read_yaml_file function returning all data into a dictionary.
def read_yaml_file(full_path=None, relative_path=None):
if relative_path is not None:
resource_file_location_local = ProjectPaths.get_project_root_path() + relative_path
else:
resource_file_location_local = full_path
with open(resource_file_location_local, 'r') as stream:
try:
file_artifacts = yaml.safe_load(stream)
except yaml.YAMLError as exc:
print(exc)
return dict(file_artifacts.items())
Upvotes: -3
Reputation: 371
To access any element of a list in a YAML file like this:
global:
registry:
url: dtr-:5000/
repoPath:
dbConnectionString: jdbc:oracle:thin:@x.x.x.x:1521:abcd
You can use following python script:
import yaml
with open("/some/path/to/yaml.file", 'r') as f:
valuesYaml = yaml.load(f, Loader=yaml.FullLoader)
print(valuesYaml['global']['dbConnectionString'])
Upvotes: 18
Reputation: 990
First install pyyaml using pip3.
Then import yaml module and load the file into a dictionary called 'my_dict':
import yaml
with open('filename.yaml') as f:
my_dict = yaml.safe_load(f)
That's all you need. Now the entire yaml file is in 'my_dict' dictionary.
Upvotes: 66
Reputation: 67
I use ruamel.yaml. Details & debate here.
from ruamel import yaml
with open(filename, 'r') as fp:
read_data = yaml.load(fp)
Usage of ruamel.yaml is compatible (with some simple solvable problems) with old usages of PyYAML and as it is stated in link I provided, use
from ruamel import yaml
instead of
import yaml
and it will fix most of your problems.
EDIT: PyYAML is not dead as it turns out, it's just maintained in a different place.
Upvotes: 3
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