Metadata-Version: 1.1
Name: sqlphile
Version: 0.4.8.6
Summary: SQL Phile
Home-page: https://gitlab.com/hansroh/sqlphile
Author: Hans Roh
Author-email: hansroh@gmail.com
License: MIT
Download-URL: https://pypi.python.org/pypi/sqlphile
Description: ==========
        SQLPhile
        ==========
        
        .. contents:: Table of Contents
        
        Introduce
        =============
        
        SQLPhile is a SQL template engine and Python style SQL generator. It looks like Django ORM but it hasn't any relationship with Django or ORM.
        
        But it is inspired by Django ORM and iBATIS SQL Maps.
        
        SQLPhile might be useful for keeping clean look of your app script. It can make hide SQL statements for your script by using Python functions or/and writing SQL templates to seperated files.
        
        For Example,
        
        .. code:: python
          
          conn = psycopg2.connect (...)
          cursor = conn.cursor ()
          cursor.execute ("""
            SELECT type, org, count(*) cnt FROM tbl_file
            WHERE org = {} AND filename LIKE '%{}'
            GROUP BY {}    
            ORDER BY {}
            LIMIT {}
            OFFSET {}
          """.format (1, 'OCD', 'type', 'org, cnt DESC', 10, 10))
          cursor.close ()
          conn.close ()
          
        This codes can be written with SQLPhile:
        
        .. code:: python
          
          import sqlphile as sp
          
          with sp.postgres ("dbname", "user", "password", "server") as db:
            q = db.select ("tbl_file").get ("type", "count(*) cnt")
            q.filter (org = 1, name__endswith = 'OCD')
            q.group_by ("type").order_by ("org", "-cnt")[10:20]
            q.execute ().fetchall ()
        
        Or you can use SQL template file: sqlmaps/file.sql:
        
        .. code:: html
        
          <sql name="get_stat">
            SELECT type, org, count(*) cnt FROM tbl_file
            WHERE {_filters} {_group_by} {_order_by} {_limit} {_offset}
          </sql>
        
        Your app code is,
          
        .. code:: python
          
          with sp.sqlite3 ("dbname.db3", dir = "./sqlmap") as db:  
            q = db.file.get_stat.filter (org = 1, name__endswith = 'OCD')
            q.group_by ("type").order_by ("org", "-cnt")[10:20]
            q.execute ().fetchall ()
        
        
        Simple Query
        --------------
        
        SQLPhile provide select(), update(), insert() and delete() for generic SQL operation.
        
        .. code:: python
          
          import sqlphile as sp
          
          with sp.sqlite3 (r"sqlite3.db3") as db:
            q = db.insert ("tbl_file")
            q.data (_id = 1, score = 1.3242, name = "file-A", moddate = datetime.date.today ())
            q.execute ()
          
            q = db.update ("tbl_file")
            q.data (name = "Jenny", modified = datetime.date.today ())
            q.filter (...)
            q.execute ()
            
            q = db.delete ("tbl_file")
            q.filter (...)
        
            q = db.select ("tbl_file")
            q.get ("id", "name", "create", "modified")
            q.filter (...)
            
            for row in q.execute ().fetchall ():
              ...
            
        If you want to insert or update to NULL value, give None.
        
        .. code:: python  
          
          q = db.insert ("tbl_file", score = None)  
          
        Filtering & Excluding
        ======================
        
        First of all, 
        
        .. code:: python
        
          q.filter (id__eq = 1, name = None)
          >> id = 1
        
        Please give your attention that *name* will be ignored. It makes reducing 'if' statements.
        
        Otherwise, filter () is very similar with Django ORM.
        
        .. code:: python
        
          q = sp.get_stat
          
          q.all ()
          >> 1 = 1
          
          q.filter (id = 1)
          >> id = 1
          
          q.filter (id = 1, user__in = ["hansroh", "janedoe"])
          >> id = 1 AND user in ("hansroh", "janedoe")
          
          q.filter (user__in = ["hansroh", "janedoe"])
          q.exclude (id__between = (100, 500), deleted = True)
          >> user in ("hansroh", "janedoe") AND NOT (id BETWEEN 100 AND 500 AND deleted = true)
          
          q.filter (t1__id = 1)
          >> t1.id = 1
          
          q.filter (id__exact = 1)
          >> id = 1
          
          q.filter (id__eq = 1)
          >> id = 1
          
          q.exclude (id = 1)
          >> NOT (id = 1)
          
          q.filter (id__neq = 1)
          >> id <> 1
          
          q.filter (t1__id__neq = 1)
          >> t1.id <> 1
          
          q.filter (id__gte = 1)
          >> id >= 1
          
          q.filter (id__lt = 1)
          >> id < 1
        
          q.filter (id__between = (10, 20))
          >> id BETWEEN 10 AND 20
          
          q.filter (name__contains = "fire")
          >> name LIKE '%fire%'
          
          q.exclude (name__contains = "fire")
          >> NOT name LIKE '%fire%'
          
          q.filter (name__startswith = "fire")
          >> name LIKE 'fire%'
          
          # escaping %
          q.filter (name__startswith = "fire%20ice")
          >> name LIKE 'fire\%20ice%'
          
          q.filter (name__endswith = "fire")
          >> name LIKE '%fire'
          
          q.filter (name__isnull = True)
          >> name IS NULL
          
          q.filter (name__isnull = False)
          >> name IS NOT NULL
          
          # PostgrSQL Only
          q.filter (name__regex = "^fires?")
          >> name ~ '^fires?'
          
        Also you can add multiple filters:
        
        .. code:: python
        
          q.filter (name__isnull = False, id = 4)
          >> name IS NOT NULL AND id = 4
        
        All filters will be joined with "AND" operator.
        
        Q Object
        ----------
          
        How can add OR operator?
        
        .. code:: python
        
          from sqlphile import Q
          
          q.filter (Q (id = 4) | Q (email__contains = "org"), name__isnull = False)
          >> name IS NOT NULL AND (id = 4 OR email LIKE '%org%')
          
        Note that Q objects are first, keywords arguments late. Also you can add seperatly.
        
        .. code:: python
        
          q.filter (name__isnull = False)
          q.filter (Q (id = 4) | Q (email__contains = "org"))
          >> (id = 4 OR email LIKE '%org%') AND name IS NOT NULL
        
        If making excluding filter with Q use tilde(*~*),
        
        .. code:: python
        
          q.filter (Q (id = 4) | ~Q (email__contains = "org"))
          >> (id = 4 OR NOT email LIKE '%org%')
        
        
        F Object
        ----------
          
        All value will be escaped or automatically add single quotes, but for comparing with other fileds use *F*.
        
        .. code:: python
        
          from sqlphile import F
          
          Q (email = F ("b.email"))
          >> email = b.email
          
          Q (email__contains = F ("org"))
          >> email LIKE '%' || org || '%'
          
        F can be be used for generic operation methods.
        
        .. code:: python
        
          q = db.update (tbl, n_view = F ("n_view + 1"))
          q.filter (...)
          cursor.execute (q.as_sql ())
        
        Ordering & Grouping
        ====================
        
        For ordering,
        
        .. code:: python
        
          q = db.select (tbl).get ("id", "name", "create", "modified")
          q.filter (...)
          q.order_by ("id", "-modified")
          >> ORDER BY id, modified DESC
        
        For grouping,  
        
        .. code:: python
        
          q = db.select (tbl).get ("name", "count(*) cnt")
          q.filter (...)
          q.group_by ("name")
          >> GROUP BY name
          
          q.having ("count(*) > 10")
          >> GROUP BY name HAVING count(*) > 10
        
        Offset & Limit
        ================
        
        For limiting record set,
        
        .. code:: python
        
          q = db.select (tbl).get ("id", "name", "create", "modified")
          q [:100]
          >> LIMIT 100
        
          q [10:30]
          >> LIMIT 20 OFFSET 10
          
        Be careful for slicing and limit count.
        
        Returning
        ============
        
        For Returning columns after insertinig or updating data,
        
        .. code:: python
        
          q = db.insert (tbl).data (name = "Hans", created = datetime.date.today ())  
          q.returning ("id", "name")
          >> RETURNING id, name
        
        Joining
        ============
        
        For joining tables,
        
        .. code:: python
        
          q = db.select ("tbl_file", "t1").join ("names", "t2", t1__name = F ("t2.name"))
          q.filter (id__gt > 100)
          q.get ("score", "t2.name")
          
          >> SELECT score, t2.name FROM tbl_file AS t1
             INNER JOIN names AS t2 ON t1.name = t2.name
             WHERE id > 100
        
        For joining with sub query,
        
        .. code:: python
        
          subq = db.select ("tbl_project").get ("name")  
          q = db.select ("tbl_file", "t1").join (subq, "t2", t1__name = F ("t2.name"))
          q.filter (id__gt = 100)
          q.get ("score", "t2.name")
          
          >> SELECT score, t2.name FROM tbl_file AS t1
             INNER JOIN (SELECT * FROM tbl_project) AS t2 ON t1.name = t2.name
             WHERE id > 100
        
        You can use 'from\_()' for update query,
        
        .. code:: python
             
          q = db.update ("tbl_file", "t1")
          q.from_ ("tbl_record", "t2", t1__id = F ("t2.id"))
          q.data (score = F ("t2.score"))
          q.filter (id = 1)
          
          >> UPDATE tbl_file AS t1 SET score = t2.score
             FROM tbl_record AS t2 ON t1.id = t2.id
             WHERE id = 1
            
        Also available,
        
        - left_join ()
        - right_join ()
        - full_join ()
        
        Transaction
        ====================
        
        .. code:: python
        
          q = db.update ("tbl_file")
          q.data (score = 5.0).filter (id = 6)
          q.execute (True)
        	>>> BEGIN TRANSACTION; 
        	      UPDATE tbl_file SET score = 5.0 WHERE id = 5; 
        	      COMMIT; 
        
        Branching
        ================
        
        You can branch your query branch() method.
        
        .. code:: python
        
          q = db.select ("tbl_file")
          q.get ("id", "name", "create", "modified")  
          
          # q2 is branched from q's current state
          q2 = q.branch ()
          
          q.filter (...)
          q2.filter (...)
          
          
        
        Using Template
        =================
        
        For simple example,
        
        .. code:: python
          
          with sp.sqlite3 (r"sqlite3.db3") as db:  
            q = db.tempate ("SELECT {columns} FROM tbl_file WHERE {_filters} {_order_by}")
            q.feed (columns = "id, name").filter (id__eq = 6).order_by ("-id")
            q.as_sql () # OR q.render ()
            >> SELECT id, name FROM tbl_file WHERE id = 6 ORDER BY id DESC
          
        If you create SQL templates in specific directory,
        
        .. code:: python
          
          with sp.sqlite3 ("sqlite3.db3", dir = "./sqlmaps", auto_reload = True) as db:
            ...
            
        SQLPhile will load all of your templates in ./sqlmaps.
        
        If you are under developing phase, set auto_reload True.
        
        Assume there is a template file named 'file.sql':
        
        .. code:: html
        
          <sqlmap version="1.0">
          
          <sql name="get_stat">
            SELECT type, org, count(*) cnt FROM tbl_file
            WHERE {_filters}
            GROUP BY type    
            ORDER BY org, cnt DESC
            {_limit} {_offset}
          </sql>
        
        It looks like XML file, BUT IT'S NOT. All tags - <sqlmap>, <sql></sql> should be started at first of line. But SQL of inside is at your own mind but I recommend give some indentation.
        
        Now you can access each sql temnplate via filename without extension and query name attribute:
          
        .. code:: python
        
          # filename.query name
          q = db.file.get_stat
          q.filter (...).order_by (...)
          
          # or
          q = db.file.get_stat.filter (...).order_by (...)
        
        Note: filename is *default.sql*, you can ommit filename.
        
        .. code:: python
        
          q = db.get_stat
          q.filter (...).order_by (...)
        
        Note 2: SHOULD NOT use starts with "select", "update", "insert", "delete" or "template" as template filename.
        
        
        For another example template is like this,
        
        .. code:: html
        
          <sqlmap version="1.0">
          
          <sql name="get_stat">
            SELECT type, org, count(*) cnt FROM tbl_file
            WHERE {_filters}
            GROUP BY type
            ORDER BY org, cnt DESC
            {_limit} {offset}
          </sql>
          
          <sql name="get_file">
            SELECT * cnt FROM tbl_file
            WHERE {_filters}
            {_order_by}
            {_limit} 
            {_offset}
          </sql>
        
        You just fill variables your query reqiures,
        
        .. code:: python
        
          q = db.file.get_file.filter (id__gte = 1000)[:20]
          q.order_by ("-id")
        
        Current reserved variables are,
        
        - _filters
        - _group_by
        - _order_by
        - _limit
        - _offset
        - _having
        - _returning
        
        
        Adding Data
        --------------
        
        data () also creates 3 variables automatically for inserting and updating purpose,
        
        - _pairs
        - _columns
        - _values
        
        .. code:: html
          
          <sql name="update_profile">
            UPDATE tbl_profile SET {_pairs} WHERE {_filters};
            INSERT INTO tbl_profile ({_columns}) VALUES ({_values});
          </sql>
        
        .. code:: python
          
          q = db.update_profile
          q.data (name = "Hans Roh", birth_year = 2000)
          q.data (email = None, age = 20)
        
        Will be rendered:
          
        .. code:: python
        
          {_columns} : name, birth_year, email, age
          {_values} : 'Hans Roh', 2000, NULL, 20
          {_pairs} : name='Hans Roh', birth_year=2000, email=NULL, age=20
        
        
        D Object
        ```````````
          
        D object convert dictionary into SQL column and value format and can feed them into SQL template.
        
        .. code:: python
          
          from sqlphile import D
          
          d = D (name = "Hans", id = 1, email = None)
          d.values
          >> 'Hans', 1, NULL
          
          d.columns
          >> name, id, email
          
          d.pairs
          >> name = 'Hans', id = 1, email = NULL
          
        And you can feed to template with prefix.
        
        .. code:: html
        
          <sql name="get_file">
            INSERT ({_columns}, {additional_columns})
            VALUES ({_valuess}, {additional_values})
            {_returning};
          </sql>
        
        In app,
          
        .. code:: python
          
          q = db.file.get_file.data (area = "730", additional = D (name = 'Hans', id = 1))
          q.returning ("id")
          q.execute ()
        
        In a conclusion, it will be created 3 variables automatically,
          
        - additional_pairs
        - additional_columns
        - additional_values
        
        More About filter()
        ---------------------
        
        In some cases, filter is tricky.
        
        .. code:: html
        
          <sqlmap version="1.0">
          
          <sql name="get_stat">
            SELECT type, org, count(*) cnt FROM tbl_file
            WHERE isdeleted is false AND {_filters}    
          </sql>
        
        Above SQL is only valid when {_filters} exists, but what if filter doesn't be provided all the time? You can write like this:
        
        .. code:: python
        
          q = db.file.get_file.filter (__all = True, id__gte = None)
          >> WHERE isdeleted is false AND 1 = 1
          
          q = db.file.get_file.filter (__all = True, id__gte = 1)
          >> WHERE isdeleted is false AND 1 = 1 AND id >= 1
        
        
        Variablize Your Query
        -----------------------
        
        You can add variable on your sql by feed() and data() and both can be called multiple times.
        
        Feeding Variable Key-Value Pairs
        ``````````````````````````````````````
        
        .. code:: html
          
          <sql name="get_file">
            SELECT {cols} FROM {tbl}
            WHERE {_filters}
          </sql>
        
        Now feed keywords args with feed ():
        
        .. code:: python
        
          q = db.file.get_file
          q.feed (cols = "id, name, created", tbl = "tbl_file")
          q.filter (id__gte = 1000)
        
        
        Also you can feed filter.
        
        .. code:: html
          
          <sql name="get_file">
            SELECT * FROM tbl_file
            WHERE {id} AND {name} AND create BETWEEN {created}
          </sql>
        
        .. code:: python
        
          q.feed (id = Q (id__in = [1,2,3,4,5]))
          >> id IN (1,2,3,4,5)
          
          q.feed (id = Q (id__in = [1,2,3,4,5]), name = "Hans")
          >> id IN (1,2,3,4,5) AND name = 'Hans'
          
          q.feed (id = Q (id__in = [1,2,3,4,5]), name = Q (name = None), created = B (1, 4))
          # name is ignored by 1 = 1
          >> id IN (1,2,3,4,5) AND 1 = 1
        
        Actually, feed () can be omitable,
        
        .. code:: python
          
          # like instance constructor
          q = db.file.get_file (cols = "id, name, created", tbl = "tbl_file")
          q.filter (id__gte = 1000)
          
        Actually this template frmating use python format function, 
        
        .. code:: html
        
          <sql name="get_file">
            SELECT * FROM tbl_file
            WHERE id = '{id:010d}' AND name = '{name:10s}'
          </sql>
        
          q.feed (id = 10000, name = 'hansroh')
          >> WHERE id = '0000010000' AND name = 'hansroh   '
          
          
        Feeding V Object
        ````````````````````
        
        If V will escape values for fitting SQL. You needn't care about sing quotes, escaping or type casting on date time field.
        
        .. code:: python
        
          V (1)
          >> 1
          
          V (__eq = 1)
          >> 1
          
          V (datetime.date.today ())
          >> TIMESTAMP '20171224 00:00:00'
          
          V ("Hans")
          >> 'Hans'
          
          V (None)
          >> NULL
          
          V ()
          >> NULL
          
          V (__eq = "Hans")
          >> 'Hans'  
          
          V (__contains = "Hans")
          >> '%Hans%'
          
          V (__in = [1,2])
          >> (1,2)
          
          V (__between = [1,2])
          >> 1 AND 2
        
        For example,
          
        .. code:: html
          
          <sql name="get_file">
            UPDATE tbl_profile
            SET {_pairs}
            WHERE id IN (
              SELECT id FROM tbl_member
              WHERE name = {name}
            );    
            UPDATE tbl_stat SET count = count + 1
            WHERE birth_year IN {birth_year};
          </sql>
        
        .. code:: python
          
          q = db.file.get_file.feed (    
            email = V ("hansroh@email.com"),
            birth_year = V (__in = (2000, 2002, 2004))
          )
          q.data (name = "Hans Roh")
        
        
        Using SQLPhile as SQL Query Generator
        =========================================
        
        If you need just SQL statement, you can use SQLPhile as template engine. 
        
        .. code:: python
        
          import sqlphle as sp
          
          template = sp.Template ("postgresql")
          q = template.select ("tbl_file").get ("score", "t2.name")
          q.as_sql () == str (q)
          
          # specify template file
          template = sp.Template ("postgresql", "./sqlmaps/test.sql")
          q = template.house (tbl = 'rc_file')
          
          # specify template directory
          template = sp.Template ("postgresql", "./sqlmaps")
          q = template.test.house (tbl = 'rc_file')
          
        
        Change Logs
        =============
        
        - 0.4
          
          - add .branch ()
          - add __regex
          - fix exclude
          - fix ~Q
          - add fetchxxx to SQL class
          - fetchxxx (as_dict = True) returns AttrDict
          - add sqlphile.Template
          
        - 0.3.5
        
          - add sp.sqlite3 and sp.postgres (== prevous sp.db3.open and qlphile.pg2.open) 
          
        - 0.3.4
          
          - extend IN query
          - enalbe multiple keyword argument for Q
            
        - 0.3.3
          
          - add db3 and pg2
          
        - 0.3.1
        
          - fix datetime type
          - add boolean type casting
          
        		
Platform: posix
Platform: nt
Classifier: License :: OSI Approved :: MIT License
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Database
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
