def generate_rst(modules_fn, types_fn):
from preql import Preql
p = Preql()
with open(types_fn, 'w', encoding='utf8') as f:
print('Preql Types', file=f)
print('===========', file=f)
for t in T.values():
try:
print(autodoc(t).print_rst(), file=f)
except NotImplementedError:
pass
with open(modules_fn, 'w', encoding='utf8') as f:
print('Preql Modules', file=f)
print('=============', file=f)
print(doc_module(p('__builtins__')).print_rst(), file=f)
p('import graph')
print(doc_module(p('graph')).print_rst(), file=f)
from ipykernel.kernelbase import Kernel
# import requests
from . import __version__
import preql
from preql.autocomplete import autocomplete
from preql import Preql, Signal
pql = Preql()
pql.set_output_format('html')
class PreqlKernel(Kernel):
implementation = 'Preql'
implementation_version = __version__
language = 'preql'
language_version = preql.__version__
language_info = {
'name': 'Preql',
'mimetype': 'text/x-pql',
'file_extension': '.pql',
'pygments_lexer': 'go',
}
banner = "Preql"
def do_execute(self,
code,
silent,
store_history=True,
user_expressions=None,
allow_stdin=False):
"""Start a Preql interactive environment with an airports table, based on a JSON url.
Uses pandas for reading and handling the JSON file.
"""
import pandas as pd
from preql import Preql
AIRPORTS_JSON_URL = 'https://gist.githubusercontent.com/tdreyno/4278655/raw/7b0762c09b519f40397e4c3e100b097d861f5588/airports.json'
airports = pd.read_json(AIRPORTS_JSON_URL)
p = Preql()
p.import_pandas(airports_full=airports)
p('''
// Remove unhelpful fields
airports = airports_full{... !url !tz !phone !email !type}
// All airports sorted by elevation (highest first)
airports_by_highest = airports order {^elev}
// Count of airports in each country, sorted by highest
airports_by_country = airports {country => airport_count: count()} order {^airport_count}
''')
p.start_repl()
def Preql(self, **kw):
settings.optimize = self.optimized
preql = Preql(self.uri, **kw)
self.preql = preql
return preql
class Vector(Base):
__tablename__ = 'Vector'
id = Column(Integer, primary_key=True)
v = Column(Integer)
VECTOR_COUNT = 1000
settings.typecheck = False
settings.cache = True
Base.metadata.create_all(engine)
Session = sessionmaker(bind=engine)
session = Session()
pql = Preql()
conn = engine.raw_connection().connection
pql._interp.state.db._conn = conn
cur = conn.cursor()
pql('''
table Vector {
id: t_id
...
}
func get(id_) = Vector[id==id_]{v}
''')
def pql_get(id_):
res = pql.get(id_).to_json()
if len(res) != 1:
---------------------------------------
test1 - simple selection and projection
* SQL : 0.010223775863647462
* Preql: 0.010765978813171387
test2 - multijoin and groupby
* SQL : 0.03636674237251282
* Preql: 0.03679810237884522
"""
import time
from preql import Preql, T
p = Preql()
p.load('../examples/chinook.pql', rel_to=__file__)
ITERS = 100
def _measure_sql(sql, iters=ITERS):
start = time.time()
for i in range(iters):
l = p._interp.state.db._backend_execute_sql(sql).fetchall()
elapsed = time.time() - start
return l, elapsed / iters
def test1():
print("test1 - simple selection and projection")
sql = r"select *, a.Title from tracks t join albums a using(AlbumId) where Title like '%r%'"
l1, elapsed = _measure_sql(sql)