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datalite3-1.0.1
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مشاهده بیشترتوضیحات
A small package that binds dataclasses to an sqlite3 database
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | datalite3-1.0.1 |
| نام | datalite3 |
| نسخه کتابخانه | 1.0.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Andrea F. Daniele |
| ایمیل نویسنده | afdaniele@ttic.edu |
| آدرس صفحه اصلی | https://github.com/afdaniele/datalite3 |
| آدرس اینترنتی | https://pypi.org/project/datalite3/ |
| مجوز | - |
# `datalite3`
[](https://pypi.python.org/pypi/datalite3/)
[](https://pypi.python.org/pypi/datalite3/)
[](https://datalite3.readthedocs.io/en/latest/?badge=latest)
It should be noted that Datalite is not suitable for secure web applications, it really is only suitable for cases when you can trust user input.
Datalite is a simple Python
package that binds your dataclasses to a table in a sqlite3 database,
using it is extremely simple, say that you have a dataclass definition,
just add the decorator `@datalite("mydb.db")` to the top of the
definition, and the dataclass will now be bound to the file `mydb.db`
[Detailed API reference](https://datalite3.readthedocs.io/en/latest/)
## Download and Install
You can install `datalite3` simply by
```shell script
pip install datalite3
```
Or you can clone the repository and run
```shell script
python setup.py
```
Datalite has no dependencies! As it is built on Python 3.6+ standard library. Albeit, its tests require `unittest` library.
## Datalite in Action
```python
from dataclasses import dataclass
from datalite3 import datalite
@datalite(db="mydb.db")
@dataclass
class Student:
student_id: int
student_name: str = "John Smith"
```
This snippet will generate a table in the sqlite3 database file `mydb.db` with
table name `student` and columns `student_id`, `student_name` with SQL types
`INTEGER` and `TEXT`, respectively. The default value for `student_name` is
`John Smith`. A third column `__id__` will be automatically added to hold the
primary key for the records.
##Basic Usage
### Entry manipulation
After creating an object traditionally, given that you used the `datalite` decorator,
the object has three new methods: `.create_entry()`, `.update_entry()`
and `.remove_entry()`, you can add the object to its associated table
using the former, and remove it using the later. You can also update a record using
the middle.
```python
student = Student(10, "Albert Einstein")
student.create_entry() # Adds the entry to the table associated in db.db.
student.student_id = 20 # Update an object on memory.
student.update_entry() # Update the corresponding record in the database.
student.remove_entry() # Removes from the table.
```
## Custom primary key
If you we want to declare one or more of the fields as part of the primary key for our
records, we can just annotate them with `Primary[type]`, where `type` can be one of
`int`, `float`, `str`, `bytes`.
```python
from dataclasses import dataclass
from datalite3 import datalite, Primary
@datalite(db="mydb.db")
@dataclass
class Student:
student_id: Primary[int]
student_name: str = "John Smith"
```
This snippet will generate a table in the sqlite3 database file `mydb.db` with
table name `student` and columns `student_id`, `student_name` with SQL types
`INTEGER` and `TEXT`, respectively. The column `student_id` will be also the primary
key and no `__id__` column will be added.
## Fetching Records
> :warning: **Limitation! Fetch can only fetch limited classes correctly**: int, float, bytes and str!
Finally, you may wish to recreate objects from a table that already exists, for
this purpose we have the `fetch` module, from this you can import `
fetch_from(class_, key)` as well as `is_fetchable(className, key)`
former fetches a record from the SQL database given its unique key
whereas the latter checks if it is fetchable (most likely to check if it exists.)
```python
>>> fetch_from(Student, 20)
Student(student_id=20, student_name='Albert Einstein')
```
We also have three helper methods:
- `fetch_all(class_)`: fetches all records of a given class. Returns a tuple of `class_` objects;
- `fetch_if(class_, condition)`: fetches all the records of type `class_` that satisfy the given
condition. Here conditions must be written is SQL syntax;
- `fetch_equals(class_, field, value)`: fetches all the records of type `class_` that have the
column `field` set to `value`;
#### Pagination
`datalite` also supports pagination on `fetch_if`, `fetch_all` and `fetch_where`,
you can specify `page` number and `element_count` for each page (default 10), for
these functions in order to get a subgroup of records.
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl datalite3-1.0.1:
pip install datalite3-1.0.1.whl
نصب پکیج tar.gz datalite3-1.0.1:
pip install datalite3-1.0.1.tar.gz