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aiosqlitedict-0.0.9
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مشاهده بیشتر
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مشاهده بیشترتوضیحات
Aiosqlitedict is a Python Wrapper for Aiosqlite.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | aiosqlitedict-0.0.9 |
| نام | aiosqlitedict |
| نسخه کتابخانه | 0.0.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Abdelrahman Sabry |
| ایمیل نویسنده | drakth5364@gmail.com |
| آدرس صفحه اصلی | https://github.com/sabrysm/aiosqlitedict |
| آدرس اینترنتی | https://pypi.org/project/aiosqlitedict/ |
| مجوز | - |
[](https://pepy.tech/project/aiosqlitedict)
Python Wrapper For sqlite3 and aiosqlite
## Main Features:
* Easy conversion between sqlite table and Python dictionary and vice-versa.
* Execute SQL queries.
* Get values of a certain column in a Python list.
* delete from your table.
* convert your json file into a sql database table.
* Order your list with parameters like ``order_by``, ``limit`` ..etc
* Choose any number of columns to your dict, which makes it faster for your dict to load instead of selecting all.
## Installation
```bash
py -m pip install -U aiosqlitedict
```
## Usage
Aiosqlite is used to import a SQLite3 table as a Python dictionary.
In this example we have a database file named ``ds_data.db`` this database has a table named ``ds_salaries``
Now to create an instance of this table in python we do the following
```python
>>> from aiosqlitedict.database import Connect
>>> ds_salaries = Connect("ds_data.db", "ds_salaries", "id")
```
now we can get rows of this table.
```python
>>> async def some_func():
...
>>> user_0 = await ds_salaries.to_dict(0, "job_title", "salary") # to get `job_title` and `salary` of user with id 0
>>> print(user_0)
{'job_title': 'Data Scientist', 'salary': 70000}
>>> user_0 = await ds_salaries.to_dict(0, "*") # to get all columns of user with id 0
>>> print(user_0)
{'id': 0, 'work_year': 2020, 'experience_level': 'MI', 'employment_type': 'FT', 'job_title': 'Data Scientist', 'salary': 70000, 'salary_currency': 'EUR', 'salary_in_usd': 79833, 'employee_residence': 'DE', 'remote_ratio': 0, 'company_location': 'DE', 'company_size': 'L'}
```
now lets do some operations on our data
```python
>>> user_0 = await ds_salaries.to_dict(0, "job_title", "salary")
>>> user_0["salary"] += 676 # increase user 0's salary
>>> print(user_0["salary"])
70676
# getting top 5 rows by salaries
>>> salaries = await ds_salaries.select("salary", limit=5, ascending=False)
>>> print(salaries)
[70000, 260000, 85000, 20000, 150000]
# to get "job_title" but order with salaries
>>> best_jobs = await ds_salaries.select("job_title", order_by="salary", limit=5, ascending=False)
>>> print(best_jobs)
['Data Scientist', 'Data Scientist', 'BI Data Analyst', 'ML Engineer', 'ML Engineer']
# We can do the same task by executing a query
>>> best_jobs_2 = await ds_salaries.execute("SELECT job_title FROM ds_salaries ORDER BY salary DESC LIMIT 5")
>>> print(best_jobs_2)
[('Data Scientist',), ('Data Scientist',), ('BI Data Analyst',), ('ML Engineer',), ('ML Engineer',)]
# to get job_titles that includes the title "scientist" without duplicates
>>> scientists = await ds_salaries.select("job_title", like="scientist", distinct=True)
>>> print(scientists)
['Data Scientist', 'Machine Learning Scientist', 'Lead Data Scientist', 'Research Scientist', 'AI Scientist', 'Principal Data Scientist', 'Applied Data Scientist', 'Applied Machine Learning Scientist', 'Staff Data Scientist']
# to get all users' salary that have the title "ML Engineer" using a query
>>> ML_Engineers = await ds_salaries.execute("SELECT salary FROM ds_salaries WHERE job_title = 'ML Engineer'")
>>> print(ML_Engineers)
[(14000,), (270000,), (7000000,), (8500000,), (256000,), (20000,)]
# to get the highest salaries
>>> high_salaries = await ds_salaries.select("salary", between=(10000000, 40000000)) # between 30M and 40M salary
>>> print(sorted(high_salaries, reverse=True))
[30400000, 11000000, 11000000]
# but what if we want to know their ids? here order_by is best used
>>> high_salaries2 = await ds_salaries.select("salary", order_by="salary", limit=3, ascending=False) # same task with different method
>>> print(high_salaries2)
[30400000, 11000000, 11000000]
>>> high_salaries3 = await ds_salaries.select("id", order_by="salary", limit=3, ascending=False) # id of richest to poorest
>>> print(high_salaries3)
[177, 7, 102]
```
| :warning: Warning: Connect.select method is vulnerable to SQL injection.|
| --- |
Lets say you want to delete a certain user
```python
>>> await ds_salaries.delete(5) # removing user with id 5 from the table.
```
finally updating our SQLite table
```python
>>> await ds_salaries.to_sql(0, user_0) # Saving user 0's data to the table
```
## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
## License
Please notice that
this package is built-on top of ``aiosqlite``
[MIT](https://github.com/sabrysm/aiosqlitedict/blob/main/LICENSE)
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.6 | Python |
نحوه نصب
نصب پکیج whl aiosqlitedict-0.0.9:
pip install aiosqlitedict-0.0.9.whl
نصب پکیج tar.gz aiosqlitedict-0.0.9:
pip install aiosqlitedict-0.0.9.tar.gz