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Adwaith-RajeshAdwaith-Rajesh
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Added docs
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‎docs/code/add.md‎

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<h1 align="center"> Onstro DB </h1>
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## Adding Data
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Values can be added to the DB with the `.add()` method. It takes a list of values to add to the DB.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad"}
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])
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db.commit() # save the changes
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print(db)
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# output
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{'70ba3370': {'name': 'ad'}}
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```
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> `db.commit()` stores all the current addition and updates in the `.db` file. If not the changes will not be permanent. The commit has no meaning if the DB is an in memory DB
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### Adding multiple values.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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ids = db.add([
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{"name": "ad"},
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{"name": "fred"}
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], get_hash_id=True)
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db.commit() # save the changes
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print(db)
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print(ids)
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# output
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{'70ba3370': {'name': 'ad'}, 'd0cfc2e5': {'name': 'fred'}}
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['70ba3370', 'd0cfc2e5']
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```
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> The `get_hash_id` param if set to `True` will return a list of all the hash id of the newly added data in the order in which they are inserted.
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---

‎docs/code/chain.md‎

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<h1 align="center"> Onstro DB </h1>
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## Multiple conditions in queries
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As you might have noticed that all the methods that accept query as an argument, the query can only be one condition long.
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In order have queries that have multiple condition you can use that following technique
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 3}
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])
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print(db)
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hid = db.get_hash_id({"name": "ad", "age": 3})
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db.update_by_hash_id(hid[0], {"name": 'mike'})
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print(db)
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```
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{ '7b672af4': {'name': 'ad', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'f3d32e1e': {'name': 'dev', 'age': 3}}
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{ '110f1f27': {'name': 'mike', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'f3d32e1e': {'name': 'dev', 'age': 3}}
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> The `get_hash_id` method returns a list of all the hash ids of rows that matches all the conditions provided in the query.

‎docs/code/delete.md‎

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## Deleting data from the DB
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There are three ways to delete data from a DB
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- delete_by_query
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- delete_by_hash_id
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- purge
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### delete_by_query
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The `delete_by_query` accepts a single condition which removes all the rows that mathes that condition
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 5}
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])
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print(db)
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db.delete_by_query({"name": "ad"}) # queries can only be one condition long(There is a work around for this)
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print(db)
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```
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{ '7b672af4': {'name': 'ad', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'41907268': {'name': 'dev', 'age': 5}}
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{'93b626d2': {'name': 'fred', 'age': 4}, '41907268': {'name': 'dev', 'age': 5}}
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### delete_by_hash_id
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The `delete_by_hash_id` taskes the hash id of the row as an argument
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 5}
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])
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print(db)
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db.delete_by_hash_id("93b626d2")
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print(db)
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```
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{ '7b672af4': {'name': 'ad', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'41907268': {'name': 'dev', 'age': 5}}
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{'7b672af4': {'name': 'ad', 'age': 3}, '41907268': {'name': 'dev', 'age': 5}}
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### purge
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Purging a DB will delete all the rows.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 5}
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])
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print(db)
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db.purge()
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db.commit() # to save the changes
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print(db)
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```
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{ '7b672af4': {'name': 'ad', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'41907268': {'name': 'dev', 'age': 5}}
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{}

‎docs/code/get.md‎

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<h1 align="center"> Onstro DB </h1>
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## Getting data from the DB
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You can get data from a DB with the following methods
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- get_by_query()
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- get_by_hash_id()
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- get_all()
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### get_by_query
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The `get_by_query` method takes a single condition query and return a dict of all the rows that matches that condition
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 3}
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])
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data = db.get_by_query({"age": 3}) # queries can only be one condition long(There is a work around for this)
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print(data)
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```
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{'7b672af4': {'name': 'ad', 'age': 3}, 'f3d32e1e': {'name': 'dev', 'age': 3}}
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### get_by_hash_id
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The `get_by_hash_id` accepts the hash id of the row that you want to get as an argument.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 3}
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])
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print(db)
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data = db.get_by_hash_id("7b672af4")
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print(data)
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```
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{ '7b672af4': {'name': 'ad', 'age': 3},
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'93b626d2': {'name': 'fred', 'age': 4},
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'f3d32e1e': {'name': 'dev', 'age': 3}}
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{'name': 'ad', 'age': 3}
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### get_all
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The `get_all` methods returns all the rows in the DB
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str", "required": True},
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"age": {"type": "int"}
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}
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db = OnstroDb(db_name="test", schema=schema)
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db.add([
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{"name": "ad", "age": 3},
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{"name": "fred", "age": 4},
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{"name": "dev", "age": 3}
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])
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data = db.get_all()
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print(data)
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```
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{'7b672af4': {'name': 'ad', 'age': 3}, '93b626d2': {'name': 'fred', 'age': 4}, 'f3d32e1e': {'name': 'dev', 'age': 3}}
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```python
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```

‎docs/code/initialize.md‎

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<h1 align="center"> Onstro DB </h1>
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### Initializing the DB
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str"}
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}
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db = OnstroDb(db_name="test", db_path="./test_db", schema=schema)
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```
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The above code snippet will create a new DB with the name `test` in the directory `test_db`. The tree structure of the directory will look something like this.
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```commandline
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`-- test_db
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`-- test
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|-- db.schema
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`-- test.db
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```
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The `db.schema` file stores the initially provided schema, thus avoiding the need to provide the schema during the second run.
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> The supported types for the schema are **int**, **str**, **bool**, **float**. and these must be in quotes.
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> if **db_path** is not provided then it will default to `./onstro-db`
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---
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### In memory DB
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To make an in memory DB, Initialize the DB as follows.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str"}
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}
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db = OnstroDb(db_name="test", schema=schema, in_memory=True)
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```
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This will not create the files as shown in the above snippet.
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---
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### Allowing duplicate values.
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The DB is designed not to have duplicate values, and if tried to insert one, will raise an error.
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In order to handle duplicate values initialize the DB as follows.
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```python
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from onstrodb import OnstroDb
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schema = {
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"name": {"type": "str"}
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}
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db = OnstroDb(db_name="test", schema=schema, allow_duplicate_values=True)
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```
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This will work with both normal and in memory DB.
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---

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