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dictquery-0.5.0.dev1
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تبلیغات ما
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مشاهده بیشترتوضیحات
Library to query python dicts
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dictquery-0.5.0.dev1 |
| نام | dictquery |
| نسخه کتابخانه | 0.5.0.dev1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Denis Lisovik |
| ایمیل نویسنده | cyberlis@rccraft.ru |
| آدرس صفحه اصلی | https://github.com/cyberlis/dictquery |
| آدرس اینترنتی | https://pypi.org/project/dictquery/ |
| مجوز | MIT |
DictQuery
========================
Library to query python dicts
Several syntax examples:
```
"age >= 12"
"`user.name` == 'cyberlis'"
"`user.email` MATCH /\w+@\w+\.com/ AND age != 11"
"`user.friends.age` > 12 AND `user.friends.name` LIKE 'Ra*ond'"
"email LIKE 'mariondelgado?bleendot?com'"
"eyeColor IN ['blue', 'green', 'black']"
"isActive AND (gender == 'female' OR age == 27)"
"latitude != longitude"
```
Supported data types
====================
| type | example |
|-----------|---------|
| KEY | name, age, \`friends.name.firstname\`, \`friends.age\` |
| NUMBER | 42, -12, 34.7 |
| STRING | 'hello', "hellow" |
| BOOLEAN | true, false |
| NONE | none, null |
| NOW | utc current datetime |
| REGEXP | /\d+\d+\w+/ |
| ARRAY | list of any items and any types |
Keys
===========
Key literals must start with a letter or an underscore, such as:
* `_underscore`
* `underscore_`
The remainder of your variable name may consist of letters, numbers and underscores.
* `password1`
* `n00b`
* `un_der_scores`
If you need a key with separator character (`.` or `/`) because you use nested keys, or need spaces or other punctuation characters in key, use back-ticks (\`\`)
DictQuery supports nested dicts splited by dot `.` or any separator specified in `key_separator` param. Default `key_separator='.'`
```
>>> import dictquery as dq
>>> dq.match(data, "`friends.age` <= 26")
True
>>> compiled = dq.compile("`friends/age` <= 26", key_separator='/')
>>> compiled.match(data)
True
```
if you don't need nested keys parsing and want get keys as is or if your keys contain separator char, you can disable nested keys behaviour by setting `use_nested_keys=False`
```
>>> import dictquery as dq
>>> dq.match(data, "`user.address`")
False
>>> dq.match(data, "age")
True
>>> compiled = dq.compile("`user.address`", use_nested_keys=False)
>>> compiled.match(data)
True
```
In query you can use dict keys 'as is' without any binary operation. DictQuery will get value by the key and evaluate it to bool
```
>>> import dictquery as dq
>>> dq.match(data, "isActive")
False
>>> dq.match(data, "isActive == false")
True
```
if key is not found by default this situation evaluates to boolean `False` (no exception raised).
You can set `raise_keyerror=True` to raise keyerror if key would not be found.
```
>>> import dictquery as dq
>>> dq.match(data, "favoriteFruit")
False
>>> compiled = dq.compile("`favoriteFruit`", raise_keyerror=True)
>>> compiled.match(data)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File ".../dictquery/dictquery/visitors.py", line 41, in match
return self.evaluate(data)
File ".../dictquery/dictquery/visitors.py", line 35, in evaluate
result = bool(self.ast.accept(self))
File ".../dictquery/dictquery/parsers.py", line 80, in accept
return visitor.visit_key(self)
File ".../dictquery/dictquery/visitors.py", line 84, in visit_key
values=self._get_dict_value(expr.value),
File ".../dictquery/dictquery/visitors.py", line 30, in _get_dict_value
self.key_separator, self.raise_keyerror)
File ".../dictquery/dictquery/datavalue.py", line 112, in query_value
raise DQKeyError("Key '{}' not found".format(data_key))
dictquery.exceptions.DQKeyError: "Key 'favoriteFruit' not found"
```
Comparisons
===========
| Operation | Meaning |
|-----------|---------|
| < | strictly less than |
| <= | less than or equal |
| > | strictly greater than |
| >= | greater than or equal |
| == | equal |
| != | not equal |
```
>>> import dictquery as dq
>>> dq.match(data, "age == 26")
True
>>> dq.match(data, "latitude > 12")
True
>>> dq.match(data, "longitude < 30")
True
>>> dq.match(data, "`friends.age` <= 26")
True
>>> dq.match(data, "longitude >= -130")
True
>>> dq.match(data, "id != 0")
True
>>> dq.match(data, "gender == 'male'")
False
```
String comparisons and matching
===============================
String literals are written in a variety of ways:
* Single quotes: 'allows embedded "double" quotes'
* Double quotes: "allows embedded 'single' quotes".
| Operation | Meaning |
|-----------|---------|
| MATCH | regexp matching |
| LIKE | glob like matching |
| IN | dict item substring in string |
| CONTAINS | dict item substring contains string |
< , <= , > , >= , == , != works same way with strings as python
```
>>> import dictquery as dq
>>> dq.match(data, "eyeColor == 'green'")
True
>>> dq.match(data, "`name.firstname` != 'Ratliff'")
True
>>> dq.match(data, "eyeColor IN 'string with green color'")
True
>>> dq.match(data, "email CONTAINS '.com'")
True
>>> dq.match(data, r"email MATCH /\w+@\w+\.\w+/")
True
>>> dq.match(data, r"email LIKE 'mariondelgado@*'")
True
>>> dq.match(data, r"email LIKE 'mariondelgado?bleendot?com'")
True
```
By default all string related operations are case sensitive. To change this behaviour you have to create instance of DictQuery with `case_sensitive=False`
```
>>> import dictquery as dq
>>> dq.match(data, "`name.firstname` == 'marion'")
False
>>> compiled = dq.compile("`name.firstname` == 'marion'", case_sensitive=False)
>>> compiled.match(data)
True
```
Array comparisons
=================
| Operation | Meaning |
|-----------|---------|
| IN | dict item in array |
| CONTAINS | dict item contains matching item |
```
>>> import dictquery as dq
>>> dq.match(data, "tags CONTAINS 'dolor'")
True
>>> dq.match(data, "eyeColor IN ['blue', 'green', 'black']")
True
```
Key presence in dict
=====================
`CONTAINS` can be used with dict items to check if key in dict
```
>>> import dictquery as dq
>>> dq.match(data, "name CONTAINS 'firstname'")
True
>>> dq.match(data, "name CONTAINS 'thirdname'")
False
```
Datetime comparisons with `NOW`
===============================
`NOW` returns current utc datetime
dict item can be compared with `NOW` using standard operations (< , <= , > , >= , == , !=)
```
>>> import dictquery as dq
>>> dq.match(data, "registered < NOW")
True
>>> dq.match(data, "registered != NOW")
True
```
Logical operators
=================
|Operator| Meaning| Example|
|--------|---------|---------|
|and |True if both the operands are true| x and y|
|or |True if either of the operands is true| x or y|
|not |True if operand is false (complements the operand)| not x |
```
>>> import dictquery as dq
>>> dq.match(data, "isActive AND gender == 'female'")
False
>>> dq.match(data, "isActive OR gender == 'female'")
True
>>> dq.match(data, "NOT isActive AND gender == 'female'")
True
```
You can use parentheses to group statements or change evaluation order
```
>>> import dictquery as dq
>>> dq.match(data, "isActive AND gender == 'female' OR age == 27")
True
>>> dq.match(data, "isActive AND (gender == 'female' OR age == 27)")
False
```
Data for examples above:
=================
```
from datetime import datetime
data = {
"_id": 10,
"isActive": False,
"age": 27,
"eyeColor": "green",
"name": {
"firstname": "Marion",
"secondname": "Delgado",
},
"gender": "female",
"email": "mariondelgado@bleendot.com",
"registered": datetime.strptime("2015-03-29T06:07:58", "%Y-%m-%dT%H:%M:%S"),
"latitude": 74.785608,
"longitude": -112.366088,
"tags": [
"voluptate",
"ex",
"dolor",
"aute"
],
"user.address": "155 Village Road, Enetai, Puerto Rico, 2634",
"friends": [
{
"id": 0,
"name": {
"firstname": "Ratliff",
"secondname": "Becker",
},
"age": 27,
"eyeColor": "green"
},
{
"id": 1,
"name": {
"firstname": "Raymond",
"secondname": "Albert",
},
"age": 19,
"eyeColor": "brown"
},
{
"id": 2,
"name": {
"firstname": "Mavis",
"secondname": "Sheppard",
},
"age": 34,
"eyeColor": "blue"
}
]
}
```
نحوه نصب
نصب پکیج whl dictquery-0.5.0.dev1:
pip install dictquery-0.5.0.dev1.whl
نصب پکیج tar.gz dictquery-0.5.0.dev1:
pip install dictquery-0.5.0.dev1.tar.gz