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pallets/flask-sqlalchemy | examples/flaskr/flaskr/auth/views.py | load_logged_in_user | def load_logged_in_user():
"""If a user id is stored in the session, load the user object from
the database into ``g.user``."""
user_id = session.get("user_id")
g.user = User.query.get(user_id) if user_id is not None else None | python | def load_logged_in_user():
"""If a user id is stored in the session, load the user object from
the database into ``g.user``."""
user_id = session.get("user_id")
g.user = User.query.get(user_id) if user_id is not None else None | [
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/auth/views.py | register | def register():
"""Register a new user.
Validates that the username is not already taken. Hashes the
password for security.
"""
if request.method == "POST":
username = request.form["username"]
password = request.form["password"]
error = None
if not username:
... | python | def register():
"""Register a new user.
Validates that the username is not already taken. Hashes the
password for security.
"""
if request.method == "POST":
username = request.form["username"]
password = request.form["password"]
error = None
if not username:
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/auth/views.py | login | def login():
"""Log in a registered user by adding the user id to the session."""
if request.method == "POST":
username = request.form["username"]
password = request.form["password"]
error = None
user = User.query.filter_by(username=username).first()
if user is None:
... | python | def login():
"""Log in a registered user by adding the user id to the session."""
if request.method == "POST":
username = request.form["username"]
password = request.form["password"]
error = None
user = User.query.filter_by(username=username).first()
if user is None:
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/blog/views.py | index | def index():
"""Show all the posts, most recent first."""
posts = Post.query.order_by(Post.created.desc()).all()
return render_template("blog/index.html", posts=posts) | python | def index():
"""Show all the posts, most recent first."""
posts = Post.query.order_by(Post.created.desc()).all()
return render_template("blog/index.html", posts=posts) | [
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/blog/views.py | get_post | def get_post(id, check_author=True):
"""Get a post and its author by id.
Checks that the id exists and optionally that the current user is
the author.
:param id: id of post to get
:param check_author: require the current user to be the author
:return: the post with author information
:rais... | python | def get_post(id, check_author=True):
"""Get a post and its author by id.
Checks that the id exists and optionally that the current user is
the author.
:param id: id of post to get
:param check_author: require the current user to be the author
:return: the post with author information
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/blog/views.py | create | def create():
"""Create a new post for the current user."""
if request.method == "POST":
title = request.form["title"]
body = request.form["body"]
error = None
if not title:
error = "Title is required."
if error is not None:
flash(error)
... | python | def create():
"""Create a new post for the current user."""
if request.method == "POST":
title = request.form["title"]
body = request.form["body"]
error = None
if not title:
error = "Title is required."
if error is not None:
flash(error)
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/blog/views.py | update | def update(id):
"""Update a post if the current user is the author."""
post = get_post(id)
if request.method == "POST":
title = request.form["title"]
body = request.form["body"]
error = None
if not title:
error = "Title is required."
if error is not Non... | python | def update(id):
"""Update a post if the current user is the author."""
post = get_post(id)
if request.method == "POST":
title = request.form["title"]
body = request.form["body"]
error = None
if not title:
error = "Title is required."
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/blog/views.py | delete | def delete(id):
"""Delete a post.
Ensures that the post exists and that the logged in user is the
author of the post.
"""
post = get_post(id)
db.session.delete(post)
db.session.commit()
return redirect(url_for("blog.index")) | python | def delete(id):
"""Delete a post.
Ensures that the post exists and that the logged in user is the
author of the post.
"""
post = get_post(id)
db.session.delete(post)
db.session.commit()
return redirect(url_for("blog.index")) | [
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pallets/flask-sqlalchemy | flask_sqlalchemy/utils.py | parse_version | def parse_version(v):
"""
Take a string version and conver it to a tuple (for easier comparison), e.g.:
"1.2.3" --> (1, 2, 3)
"1.2" --> (1, 2, 0)
"1" --> (1, 0, 0)
"""
parts = v.split(".")
# Pad the list to make sure there is three elements so that we get maj... | python | def parse_version(v):
"""
Take a string version and conver it to a tuple (for easier comparison), e.g.:
"1.2.3" --> (1, 2, 3)
"1.2" --> (1, 2, 0)
"1" --> (1, 0, 0)
"""
parts = v.split(".")
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SignallingSession.get_bind | def get_bind(self, mapper=None, clause=None):
"""Return the engine or connection for a given model or
table, using the ``__bind_key__`` if it is set.
"""
# mapper is None if someone tries to just get a connection
if mapper is not None:
try:
# SA >= 1.3... | python | def get_bind(self, mapper=None, clause=None):
"""Return the engine or connection for a given model or
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | Pagination.pages | def pages(self):
"""The total number of pages"""
if self.per_page == 0 or self.total is None:
pages = 0
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pages = int(ceil(self.total / float(self.per_page)))
return pages | python | def pages(self):
"""The total number of pages"""
if self.per_page == 0 or self.total is None:
pages = 0
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pages = int(ceil(self.total / float(self.per_page)))
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | Pagination.next | def next(self, error_out=False):
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assert self.query is not None, 'a query object is required ' \
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | BaseQuery.get_or_404 | def get_or_404(self, ident, description=None):
"""Like :meth:`get` but aborts with 404 if not found instead of returning ``None``."""
rv = self.get(ident)
if rv is None:
abort(404, description=description)
return rv | python | def get_or_404(self, ident, description=None):
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rv = self.get(ident)
if rv is None:
abort(404, description=description)
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"""Like :meth:`first` but aborts with 404 if not found instead of returning ``None``."""
rv = self.first()
if rv is None:
abort(404, description=description)
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"""Like :meth:`first` but aborts with 404 if not found instead of returning ``None``."""
rv = self.first()
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abort(404, description=description)
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | BaseQuery.paginate | def paginate(self, page=None, per_page=None, error_out=True, max_per_page=None, count=True):
"""Returns ``per_page`` items from page ``page``.
If ``page`` or ``per_page`` are ``None``, they will be retrieved from
the request query. If ``max_per_page`` is specified, ``per_page`` will
be ... | python | def paginate(self, page=None, per_page=None, error_out=True, max_per_page=None, count=True):
"""Returns ``per_page`` items from page ``page``.
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.create_scoped_session | def create_scoped_session(self, options=None):
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on the factory from :meth:`create_session`.
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... | python | def create_scoped_session(self, options=None):
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.make_declarative_base | def make_declarative_base(self, model, metadata=None):
"""Creates the declarative base that all models will inherit from.
:param model: base model class (or a tuple of base classes) to pass
to :func:`~sqlalchemy.ext.declarative.declarative_base`. Or a class
returned from ``decla... | python | def make_declarative_base(self, model, metadata=None):
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.init_app | def init_app(self, app):
"""This callback can be used to initialize an application for the
use with this database setup. Never use a database in the context
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leak.
"""
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"""This callback can be used to initialize an application for the
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.apply_driver_hacks | def apply_driver_hacks(self, app, sa_url, options):
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.make_connector | def make_connector(self, app=None, bind=None):
"""Creates the connector for a given state and bind."""
return _EngineConnector(self, self.get_app(app), bind) | python | def make_connector(self, app=None, bind=None):
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.get_engine | def get_engine(self, app=None, bind=None):
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state = get_state(app)
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connector = state.connectors.get(bind)
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connector = self.make_connector(app, ... | python | def get_engine(self, app=None, bind=None):
"""Returns a specific engine."""
app = self.get_app(app)
state = get_state(app)
with self._engine_lock:
connector = state.connectors.get(bind)
if connector is None:
connector = self.make_connector(app, ... | [
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.get_app | def get_app(self, reference_app=None):
"""Helper method that implements the logic to look up an
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if reference_app is not None:
return reference_app
if current_app:
return current_app._get_current_object()
if self.app is not None:
... | python | def get_app(self, reference_app=None):
"""Helper method that implements the logic to look up an
application."""
if reference_app is not None:
return reference_app
if current_app:
return current_app._get_current_object()
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.get_tables_for_bind | def get_tables_for_bind(self, bind=None):
"""Returns a list of all tables relevant for a bind."""
result = []
for table in itervalues(self.Model.metadata.tables):
if table.info.get('bind_key') == bind:
result.append(table)
return result | python | def get_tables_for_bind(self, bind=None):
"""Returns a list of all tables relevant for a bind."""
result = []
for table in itervalues(self.Model.metadata.tables):
if table.info.get('bind_key') == bind:
result.append(table)
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.get_binds | def get_binds(self, app=None):
"""Returns a dictionary with a table->engine mapping.
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"""
app = self.get_app(app)
binds = [None] + list(app.config.get('SQLALCHEMY_BINDS') or ())
retval = {}
for bin... | python | def get_binds(self, app=None):
"""Returns a dictionary with a table->engine mapping.
This is suitable for use of sessionmaker(binds=db.get_binds(app)).
"""
app = self.get_app(app)
binds = [None] + list(app.config.get('SQLALCHEMY_BINDS') or ())
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pallets/flask-sqlalchemy | flask_sqlalchemy/__init__.py | SQLAlchemy.reflect | def reflect(self, bind='__all__', app=None):
"""Reflects tables from the database.
.. versionchanged:: 0.12
Parameters were added
"""
self._execute_for_all_tables(app, bind, 'reflect', skip_tables=True) | python | def reflect(self, bind='__all__', app=None):
"""Reflects tables from the database.
.. versionchanged:: 0.12
Parameters were added
"""
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pallets/flask-sqlalchemy | examples/flaskr/flaskr/__init__.py | create_app | def create_app(test_config=None):
"""Create and configure an instance of the Flask application."""
app = Flask(__name__, instance_relative_config=True)
# some deploy systems set the database url in the environ
db_url = os.environ.get("DATABASE_URL")
if db_url is None:
# default to a sqlite... | python | def create_app(test_config=None):
"""Create and configure an instance of the Flask application."""
app = Flask(__name__, instance_relative_config=True)
# some deploy systems set the database url in the environ
db_url = os.environ.get("DATABASE_URL")
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robertmartin8/PyPortfolioOpt | pypfopt/objective_functions.py | negative_sharpe | def negative_sharpe(
weights, expected_returns, cov_matrix, gamma=0, risk_free_rate=0.02
):
"""
Calculate the negative Sharpe ratio of a portfolio
:param weights: asset weights of the portfolio
:type weights: np.ndarray
:param expected_returns: expected return of each asset
:type expected_r... | python | def negative_sharpe(
weights, expected_returns, cov_matrix, gamma=0, risk_free_rate=0.02
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"""
Calculate the negative Sharpe ratio of a portfolio
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:type weights: np.ndarray
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robertmartin8/PyPortfolioOpt | pypfopt/objective_functions.py | volatility | def volatility(weights, cov_matrix, gamma=0):
"""
Calculate the volatility of a portfolio. This is actually a misnomer because
the function returns variance, which is technically the correct objective
function when minimising volatility.
:param weights: asset weights of the portfolio
:type weig... | python | def volatility(weights, cov_matrix, gamma=0):
"""
Calculate the volatility of a portfolio. This is actually a misnomer because
the function returns variance, which is technically the correct objective
function when minimising volatility.
:param weights: asset weights of the portfolio
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robertmartin8/PyPortfolioOpt | pypfopt/objective_functions.py | negative_cvar | def negative_cvar(weights, returns, s=10000, beta=0.95, random_state=None):
"""
Calculate the negative CVaR. Though we want the "min CVaR portfolio", we
actually need to maximise the expected return of the worst q% cases, thus
we need this value to be negative.
:param weights: asset weights of the ... | python | def negative_cvar(weights, returns, s=10000, beta=0.95, random_state=None):
"""
Calculate the negative CVaR. Though we want the "min CVaR portfolio", we
actually need to maximise the expected return of the worst q% cases, thus
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robertmartin8/PyPortfolioOpt | pypfopt/expected_returns.py | mean_historical_return | def mean_historical_return(prices, frequency=252):
"""
Calculate annualised mean (daily) historical return from input (daily) asset prices.
:param prices: adjusted closing prices of the asset, each row is a date
and each column is a ticker/id.
:type prices: pd.DataFrame
:param fr... | python | def mean_historical_return(prices, frequency=252):
"""
Calculate annualised mean (daily) historical return from input (daily) asset prices.
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robertmartin8/PyPortfolioOpt | pypfopt/expected_returns.py | ema_historical_return | def ema_historical_return(prices, frequency=252, span=500):
"""
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:param prices: adjusted closing prices of the asset, each row is a date
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... | python | def ema_historical_return(prices, frequency=252, span=500):
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.max_sharpe | def max_sharpe(self, risk_free_rate=0.02):
"""
Maximise the Sharpe Ratio. The result is also referred to as the tangency portfolio,
as it is the tangent to the efficient frontier curve that intercepts the risk-free
rate.
:param risk_free_rate: risk-free rate of borrowing/lending... | python | def max_sharpe(self, risk_free_rate=0.02):
"""
Maximise the Sharpe Ratio. The result is also referred to as the tangency portfolio,
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.min_volatility | def min_volatility(self):
"""
Minimise volatility.
:return: asset weights for the volatility-minimising portfolio
:rtype: dict
"""
args = (self.cov_matrix, self.gamma)
result = sco.minimize(
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x0=self.initial_... | python | def min_volatility(self):
"""
Minimise volatility.
:return: asset weights for the volatility-minimising portfolio
:rtype: dict
"""
args = (self.cov_matrix, self.gamma)
result = sco.minimize(
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.custom_objective | def custom_objective(self, objective_function, *args):
"""
Optimise some objective function. While an implicit requirement is that the function
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"""
Optimise some objective function. While an implicit requirement is that the function
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.efficient_risk | def efficient_risk(self, target_risk, risk_free_rate=0.02, market_neutral=False):
"""
Calculate the Sharpe-maximising portfolio for a given volatility (i.e max return
for a target risk).
:param target_risk: the desired volatility of the resulting portfolio.
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"""
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.efficient_return | def efficient_return(self, target_return, market_neutral=False):
"""
Calculate the 'Markowitz portfolio', minimising volatility for a given target return.
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"""
Calculate the 'Markowitz portfolio', minimising volatility for a given target return.
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robertmartin8/PyPortfolioOpt | pypfopt/efficient_frontier.py | EfficientFrontier.portfolio_performance | def portfolio_performance(self, verbose=False, risk_free_rate=0.02):
"""
After optimising, calculate (and optionally print) the performance of the optimal
portfolio. Currently calculates expected return, volatility, and the Sharpe ratio.
:param verbose: whether performance should be pri... | python | def portfolio_performance(self, verbose=False, risk_free_rate=0.02):
"""
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robertmartin8/PyPortfolioOpt | pypfopt/base_optimizer.py | portfolio_performance | def portfolio_performance(
expected_returns, cov_matrix, weights, verbose=False, risk_free_rate=0.02
):
"""
After optimising, calculate (and optionally print) the performance of the optimal
portfolio. Currently calculates expected return, volatility, and the Sharpe ratio.
:param expected_returns: e... | python | def portfolio_performance(
expected_returns, cov_matrix, weights, verbose=False, risk_free_rate=0.02
):
"""
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robertmartin8/PyPortfolioOpt | pypfopt/base_optimizer.py | BaseOptimizer.clean_weights | def clean_weights(self, cutoff=1e-4, rounding=5):
"""
Helper method to clean the raw weights, setting any weights whose absolute
values are below the cutoff to zero, and rounding the rest.
:param cutoff: the lower bound, defaults to 1e-4
:type cutoff: float, optional
:pa... | python | def clean_weights(self, cutoff=1e-4, rounding=5):
"""
Helper method to clean the raw weights, setting any weights whose absolute
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robertmartin8/PyPortfolioOpt | pypfopt/base_optimizer.py | BaseScipyOptimizer._make_valid_bounds | def _make_valid_bounds(self, test_bounds):
"""
Private method: process input bounds into a form acceptable by scipy.optimize,
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:param test_bounds: minimum and maximum weight of an asset
:type test_bounds: tuple
:raises ValueError: if... | python | def _make_valid_bounds(self, test_bounds):
"""
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robertmartin8/PyPortfolioOpt | pypfopt/discrete_allocation.py | portfolio | def portfolio(weights, latest_prices, min_allocation=0.01, total_portfolio_value=10000):
"""
For a long only portfolio, convert the continuous weights to a discrete allocation
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"""
For a long only portfolio, convert the continuous weights to a discrete allocation
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robertmartin8/PyPortfolioOpt | pypfopt/discrete_allocation.py | portfolio_lp | def portfolio_lp(
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"""
For a long only portfolio, convert the continuous weights to a discrete allocation
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robertmartin8/PyPortfolioOpt | pypfopt/discrete_allocation.py | portfolio_byvalue | def portfolio_byvalue(
weights, steps, min_values, max_values=1e9, total_portfolio_value=10000
):
"""
For a long only portfolio, convert the continuous weights to a discrete
allocation using Mixed Integer Linear Programming. This function assumes
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weights, steps, min_values, max_values=1e9, total_portfolio_value=10000
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For a long only portfolio, convert the continuous weights to a discrete
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robertmartin8/PyPortfolioOpt | pypfopt/value_at_risk.py | CVAROpt.min_cvar | def min_cvar(self, s=10000, beta=0.95, random_state=None):
"""
Find the portfolio weights that minimises the CVaR, via
Monte Carlo sampling from the return distribution.
:param s: number of bootstrap draws, defaults to 10000
:type s: int, optional
:param beta: "significa... | python | def min_cvar(self, s=10000, beta=0.95, random_state=None):
"""
Find the portfolio weights that minimises the CVaR, via
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | sample_cov | def sample_cov(prices, frequency=252):
"""
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:param prices: adjusted closing prices of the asset, each row is a date
and each column is a ticker/id.
:type prices: pd.DataFrame
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"""
Calculate the annualised sample covariance matrix of (daily) asset returns.
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | semicovariance | def semicovariance(prices, benchmark=0, frequency=252):
"""
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the returns are less than the benchmark.
.. semicov = E([min(r_i - B, 0)] . [min(r_j - B, 0)])
:param prices: adjusted closing prices of the asset, each row is a date
... | python | def semicovariance(prices, benchmark=0, frequency=252):
"""
Estimate the semicovariance matrix, i.e the covariance given that
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | _pair_exp_cov | def _pair_exp_cov(X, Y, span=180):
"""
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:param X: first time series of returns
:type X: pd.Series
:param Y: second time series of returns
:type Y: pd.Series
:param span: the span of the exponential weighting function, de... | python | def _pair_exp_cov(X, Y, span=180):
"""
Calculate the exponential covariance between two timeseries of returns.
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:type X: pd.Series
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | exp_cov | def exp_cov(prices, span=180, frequency=252):
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Estimate the exponentially-weighted covariance matrix, which gives
greater weight to more recent data.
:param prices: adjusted closing prices of the asset, each row is a date
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:type prices: pd.DataFr... | python | def exp_cov(prices, span=180, frequency=252):
"""
Estimate the exponentially-weighted covariance matrix, which gives
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Calculate the minimum covariance determinant, an estimator of the covariance matrix
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:param prices: adjusted closing prices of the asset, each row is a date
and each column is a ticker... | python | def min_cov_determinant(prices, frequency=252, random_state=None):
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Shrink a sample covariance matrix to the identity matrix (scaled by the average
sample variance). This method does not estimate an optimal shrinkage parameter,
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:param delta: shrinkage parameter, defaults to 0.... | python | def shrunk_covariance(self, delta=0.2):
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Shrink a sample covariance matrix to the identity matrix (scaled by the average
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"""
Calculate the Ledoit-Wolf shrinkage estimate.
:return: shrunk sample covariance matrix
:rtype: np.ndarray
"""
X = np.nan_to_num(self.X.values)
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"""
Calculate the Ledoit-Wolf shrinkage estimate.
:return: shrunk sample covariance matrix
:rtype: np.ndarray
"""
X = np.nan_to_num(self.X.values)
shrunk_cov, self.delta = covariance.ledoit_wolf(X)
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | CovarianceShrinkage.oracle_approximating | def oracle_approximating(self):
"""
Calculate the Oracle Approximating Shrinkage estimate
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:rtype: np.ndarray
"""
X = np.nan_to_num(self.X.values)
shrunk_cov, self.delta = covariance.oas(X)
return self.format_and_an... | python | def oracle_approximating(self):
"""
Calculate the Oracle Approximating Shrinkage estimate
:return: shrunk sample covariance matrix
:rtype: np.ndarray
"""
X = np.nan_to_num(self.X.values)
shrunk_cov, self.delta = covariance.oas(X)
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | ConstantCorrelation.shrink | def shrink(self):
"""
Calculate the Constant-Correlation covariance matrix.
:return: shrunk sample covariance matrix
:rtype: np.ndarray
"""
x = np.nan_to_num(self.X.values)
# de-mean returns
t, n = np.shape(x)
meanx = x.mean(axis=0)
x = x... | python | def shrink(self):
"""
Calculate the Constant-Correlation covariance matrix.
:return: shrunk sample covariance matrix
:rtype: np.ndarray
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x = np.nan_to_num(self.X.values)
# de-mean returns
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robertmartin8/PyPortfolioOpt | pypfopt/risk_models.py | SingleIndex.shrink | def shrink(self):
"""
Calculate the Constant-Correlation covariance matrix.
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:rtype: np.ndarray
"""
x = np.nan_to_num(self.X.values)
# de-mean returns
t, n = np.shape(x)
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x = x... | python | def shrink(self):
"""
Calculate the Constant-Correlation covariance matrix.
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robertmartin8/PyPortfolioOpt | pypfopt/cla.py | CLA.min_volatility | def min_volatility(self):
"""Get the minimum variance solution"""
if not self.w:
self.solve()
var = []
for w in self.w:
a = np.dot(np.dot(w.T, self.cov_matrix), w)
var.append(a)
# return min(var)**.5, self.w[var.index(min(var))]
self.we... | python | def min_volatility(self):
"""Get the minimum variance solution"""
if not self.w:
self.solve()
var = []
for w in self.w:
a = np.dot(np.dot(w.T, self.cov_matrix), w)
var.append(a)
# return min(var)**.5, self.w[var.index(min(var))]
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robertmartin8/PyPortfolioOpt | pypfopt/cla.py | CLA.max_sharpe | def max_sharpe(self):
"""Get the max Sharpe ratio portfolio"""
if not self.w:
self.solve()
# 1) Compute the local max SR portfolio between any two neighbor turning points
w_sr, sr = [], []
for i in range(len(self.w) - 1):
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"""Get the max Sharpe ratio portfolio"""
if not self.w:
self.solve()
# 1) Compute the local max SR portfolio between any two neighbor turning points
w_sr, sr = [], []
for i in range(len(self.w) - 1):
w0 = np.copy(self.w[i])
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robertmartin8/PyPortfolioOpt | pypfopt/cla.py | CLA.efficient_frontier | def efficient_frontier(self, points):
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"""Get the efficient frontier"""
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# remove the 1, to avoid duplications
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | emit | def emit(event, *args, **kwargs):
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"""Emit a SocketIO event.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | send | def send(message, **kwargs):
"""Send a SocketIO message.
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version of ``emit()``, which should be preferred. This is a function that
can only be called from a ... | python | def send(message, **kwargs):
"""Send a SocketIO message.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | join_room | def join_room(room, sid=None, namespace=None):
"""Join a room.
This function puts the user in a room, under the current namespace. The
user and the namespace are obtained from the event context. This is a
function that can only be called from a SocketIO event handler. Example::
@socketio.on('j... | python | def join_room(room, sid=None, namespace=None):
"""Join a room.
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user and the namespace are obtained from the event context. This is a
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | leave_room | def leave_room(room, sid=None, namespace=None):
"""Leave a room.
This function removes the user from a room, under the current namespace.
The user and the namespace are obtained from the event context. Example::
@socketio.on('leave')
def on_leave(data):
username = session['user... | python | def leave_room(room, sid=None, namespace=None):
"""Leave a room.
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@socketio.on('leave')
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | close_room | def close_room(room, namespace=None):
"""Close a room.
This function removes any users that are in the given room and then deletes
the room from the server.
:param room: The name of the room to close.
:param namespace: The namespace for the room. If not provided, the
namespac... | python | def close_room(room, namespace=None):
"""Close a room.
This function removes any users that are in the given room and then deletes
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:param room: The name of the room to close.
:param namespace: The namespace for the room. If not provided, the
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | rooms | def rooms(sid=None, namespace=None):
"""Return a list of the rooms the client is in.
This function returns all the rooms the client has entered, including its
own room, assigned by the Socket.IO server.
:param sid: The session id of the client. If not provided, the client is
obtained f... | python | def rooms(sid=None, namespace=None):
"""Return a list of the rooms the client is in.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | disconnect | def disconnect(sid=None, namespace=None, silent=False):
"""Disconnect the client.
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this call the client will receive a disconnect event. Example::
@socketio.on('message')
def receive_message(msg):
if is_bann... | python | def disconnect(sid=None, namespace=None, silent=False):
"""Disconnect the client.
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@socketio.on('message')
def receive_message(msg):
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.on | def on(self, message, namespace=None):
"""Decorator to register a SocketIO event handler.
This decorator must be applied to SocketIO event handlers. Example::
@socketio.on('my event', namespace='/chat')
def handle_my_custom_event(json):
print('received json: ' +... | python | def on(self, message, namespace=None):
"""Decorator to register a SocketIO event handler.
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@socketio.on('my event', namespace='/chat')
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.on_error | def on_error(self, namespace=None):
"""Decorator to define a custom error handler for SocketIO events.
This decorator can be applied to a function that acts as an error
handler for a namespace. This handler will be invoked when a SocketIO
event handler raises an exception. The handler f... | python | def on_error(self, namespace=None):
"""Decorator to define a custom error handler for SocketIO events.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.on_error_default | def on_error_default(self, exception_handler):
"""Decorator to define a default error handler for SocketIO events.
This decorator can be applied to a function that acts as a default
error handler for any namespaces that do not have a specific handler.
Example::
@socketio.on... | python | def on_error_default(self, exception_handler):
"""Decorator to define a default error handler for SocketIO events.
This decorator can be applied to a function that acts as a default
error handler for any namespaces that do not have a specific handler.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.on_event | def on_event(self, message, handler, namespace=None):
"""Register a SocketIO event handler.
``on_event`` is the non-decorator version of ``'on'``.
Example::
def on_foo_event(json):
print('received json: ' + str(json))
socketio.on_event('my event', on_f... | python | def on_event(self, message, handler, namespace=None):
"""Register a SocketIO event handler.
``on_event`` is the non-decorator version of ``'on'``.
Example::
def on_foo_event(json):
print('received json: ' + str(json))
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.emit | def emit(self, event, *args, **kwargs):
"""Emit a server generated SocketIO event.
This function emits a SocketIO event to one or more connected clients.
A JSON blob can be attached to the event as payload. This function can
be used outside of a SocketIO event context, so it is appropri... | python | def emit(self, event, *args, **kwargs):
"""Emit a server generated SocketIO event.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.send | def send(self, data, json=False, namespace=None, room=None,
callback=None, include_self=True, skip_sid=None, **kwargs):
"""Send a server-generated SocketIO message.
This function sends a simple SocketIO message to one or more connected
clients. The message can be a string or a JSON... | python | def send(self, data, json=False, namespace=None, room=None,
callback=None, include_self=True, skip_sid=None, **kwargs):
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.run | def run(self, app, host=None, port=None, **kwargs):
"""Run the SocketIO web server.
:param app: The Flask application instance.
:param host: The hostname or IP address for the server to listen on.
Defaults to 127.0.0.1.
:param port: The port number for the server to... | python | def run(self, app, host=None, port=None, **kwargs):
"""Run the SocketIO web server.
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.stop | def stop(self):
"""Stop a running SocketIO web server.
This method must be called from a HTTP or SocketIO handler function.
"""
if self.server.eio.async_mode == 'threading':
func = flask.request.environ.get('werkzeug.server.shutdown')
if func:
fun... | python | def stop(self):
"""Stop a running SocketIO web server.
This method must be called from a HTTP or SocketIO handler function.
"""
if self.server.eio.async_mode == 'threading':
func = flask.request.environ.get('werkzeug.server.shutdown')
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miguelgrinberg/Flask-SocketIO | flask_socketio/__init__.py | SocketIO.start_background_task | def start_background_task(self, target, *args, **kwargs):
"""Start a background task using the appropriate async model.
This is a utility function that applications can use to start a
background task using the method that is compatible with the
selected async mode.
:param targe... | python | def start_background_task(self, target, *args, **kwargs):
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This is a utility function that applications can use to start a
background task using the method that is compatible with the
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miguelgrinberg/Flask-SocketIO | flask_socketio/namespace.py | Namespace.trigger_event | def trigger_event(self, event, *args):
"""Dispatch an event to the proper handler method.
In the most common usage, this method is not overloaded by subclasses,
as it performs the routing of events to methods. However, this
method can be overriden if special dispatching rules are needed... | python | def trigger_event(self, event, *args):
"""Dispatch an event to the proper handler method.
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miguelgrinberg/Flask-SocketIO | flask_socketio/namespace.py | Namespace.emit | def emit(self, event, data=None, room=None, include_self=True,
namespace=None, callback=None):
"""Emit a custom event to one or more connected clients."""
return self.socketio.emit(event, data, room=room,
include_self=include_self,
... | python | def emit(self, event, data=None, room=None, include_self=True,
namespace=None, callback=None):
"""Emit a custom event to one or more connected clients."""
return self.socketio.emit(event, data, room=room,
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miguelgrinberg/Flask-SocketIO | flask_socketio/namespace.py | Namespace.send | def send(self, data, room=None, include_self=True, namespace=None,
callback=None):
"""Send a message to one or more connected clients."""
return self.socketio.send(data, room=room, include_self=include_self,
namespace=namespace or self.namespace,
... | python | def send(self, data, room=None, include_self=True, namespace=None,
callback=None):
"""Send a message to one or more connected clients."""
return self.socketio.send(data, room=room, include_self=include_self,
namespace=namespace or self.namespace,
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miguelgrinberg/Flask-SocketIO | flask_socketio/namespace.py | Namespace.close_room | def close_room(self, room, namespace=None):
"""Close a room."""
return self.socketio.close_room(room=room,
namespace=namespace or self.namespace) | python | def close_room(self, room, namespace=None):
"""Close a room."""
return self.socketio.close_room(room=room,
namespace=namespace or self.namespace) | [
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miguelgrinberg/Flask-SocketIO | example/app.py | background_thread | def background_thread():
"""Example of how to send server generated events to clients."""
count = 0
while True:
socketio.sleep(10)
count += 1
socketio.emit('my_response',
{'data': 'Server generated event', 'count': count},
namespace='/test'... | python | def background_thread():
"""Example of how to send server generated events to clients."""
count = 0
while True:
socketio.sleep(10)
count += 1
socketio.emit('my_response',
{'data': 'Server generated event', 'count': count},
namespace='/test'... | [
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polyaxon/polyaxon | polyaxon/pipelines/celery_task.py | OperationTask.on_failure | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""Update query status and send email notification to a user"""
super().on_failure(exc, task_id, args, kwargs, einfo)
if isinstance(exc, OperationRunDoesNotExist):
return
self._operation_run.on_failure() | python | def on_failure(self, exc, task_id, args, kwargs, einfo):
"""Update query status and send email notification to a user"""
super().on_failure(exc, task_id, args, kwargs, einfo)
if isinstance(exc, OperationRunDoesNotExist):
return
self._operation_run.on_failure() | [
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polyaxon/polyaxon | polyaxon/pipelines/celery_task.py | OperationTask.on_success | def on_success(self, retval, task_id, args, kwargs):
"""Send email notification and a file, if requested to do so by a user"""
super().on_success(retval, task_id, args, kwargs)
self._operation_run.on_success() | python | def on_success(self, retval, task_id, args, kwargs):
"""Send email notification and a file, if requested to do so by a user"""
super().on_success(retval, task_id, args, kwargs)
self._operation_run.on_success() | [
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polyaxon/polyaxon | polyaxon/auditor/service.py | AuditorService.record_event | def record_event(self, event: Event) -> None:
"""
Record the event async.
"""
from polyaxon.celery_api import celery_app
from polyaxon.settings import EventsCeleryTasks
if not event.ref_id:
event.ref_id = self.get_ref_id()
serialized_event = event.ser... | python | def record_event(self, event: Event) -> None:
"""
Record the event async.
"""
from polyaxon.celery_api import celery_app
from polyaxon.settings import EventsCeleryTasks
if not event.ref_id:
event.ref_id = self.get_ref_id()
serialized_event = event.ser... | [
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polyaxon/polyaxon | polyaxon/event_manager/event_manager.py | EventManager.user_write_events | def user_write_events(self) -> List[str]:
"""Return event types where use acted on an object.
The write events are events with actions:
* CREATED
* UPDATED
* DELETED
* RESUMED
* COPIED
* CLONED
* STOPPED
"""
... | python | def user_write_events(self) -> List[str]:
"""Return event types where use acted on an object.
The write events are events with actions:
* CREATED
* UPDATED
* DELETED
* RESUMED
* COPIED
* CLONED
* STOPPED
"""
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polyaxon/polyaxon | polyaxon/event_manager/event_manager.py | EventManager.user_view_events | def user_view_events(self) -> List[str]:
"""Return event types where use viewed a main object."""
return [event_type for event_type, event in self.items if event.get_event_action()
== event_actions.VIEWED] | python | def user_view_events(self) -> List[str]:
"""Return event types where use viewed a main object."""
return [event_type for event_type, event in self.items if event.get_event_action()
== event_actions.VIEWED] | [
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polyaxon/polyaxon | polyaxon/api/users/validators.py | validate_new_email | def validate_new_email(email):
"""Validates a "new" email address by checking if it is already used by other users."""
email = normalize_email(email)
User = get_user_model() # noqa
if User.objects.filter(email=email).exists():
raise ValidationError('The given email address is already registered... | python | def validate_new_email(email):
"""Validates a "new" email address by checking if it is already used by other users."""
email = normalize_email(email)
User = get_user_model() # noqa
if User.objects.filter(email=email).exists():
raise ValidationError('The given email address is already registered... | [
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polyaxon/polyaxon | polyaxon/scheduler/spawners/templates/project_jobs/pods.py | get_project_pod_spec | def get_project_pod_spec(volume_mounts,
volumes,
image,
command,
args,
ports,
env_vars=None,
env_from=None,
container_na... | python | def get_project_pod_spec(volume_mounts,
volumes,
image,
command,
args,
ports,
env_vars=None,
env_from=None,
container_na... | [
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polyaxon/polyaxon | polyaxon/api/endpoint/base.py | BaseEndpoint.get_object | def get_object(self):
"""We memoize the access to this function in case a second call is made."""
if self._object:
return self._object
self._object = super().get_object()
if not self.AUDITOR_EVENT_TYPES:
return self._object
method = self.request.method
... | python | def get_object(self):
"""We memoize the access to this function in case a second call is made."""
if self._object:
return self._object
self._object = super().get_object()
if not self.AUDITOR_EVENT_TYPES:
return self._object
method = self.request.method
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polyaxon/polyaxon | polyaxon/api/endpoint/base.py | BaseEndpoint.initialize_context | def initialize_context(self, request: HttpRequest, *args, **kwargs) -> None:
"""
Initializes the endpoint with the context keys based on the passed
and/or based on the query parameters (request.GET).
"""
for key in self.CONTEXT_KEYS:
setattr(self, key, kwargs.get(key)... | python | def initialize_context(self, request: HttpRequest, *args, **kwargs) -> None:
"""
Initializes the endpoint with the context keys based on the passed
and/or based on the query parameters (request.GET).
"""
for key in self.CONTEXT_KEYS:
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polyaxon/polyaxon | polyaxon/scheduler/spawners/templates/volumes.py | get_shm_volumes | def get_shm_volumes():
"""
Mount an tmpfs volume to /dev/shm.
This will set /dev/shm size to half of the RAM of node.
By default, /dev/shm is very small, only 64MB.
Some experiments will fail due to lack of share memory,
such as some experiments running on Pytorch.
"""
volumes, volume_mo... | python | def get_shm_volumes():
"""
Mount an tmpfs volume to /dev/shm.
This will set /dev/shm size to half of the RAM of node.
By default, /dev/shm is very small, only 64MB.
Some experiments will fail due to lack of share memory,
such as some experiments running on Pytorch.
"""
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polyaxon/polyaxon | polyaxon/db/models/experiments.py | Experiment.last_job_statuses | def last_job_statuses(self) -> List[str]:
"""The last constants of the job in this experiment."""
statuses = []
for status in self.jobs.values_list('status__status', flat=True):
if status is not None:
statuses.append(status)
return statuses | python | def last_job_statuses(self) -> List[str]:
"""The last constants of the job in this experiment."""
statuses = []
for status in self.jobs.values_list('status__status', flat=True):
if status is not None:
statuses.append(status)
return statuses | [
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polyaxon/polyaxon | polyaxon/db/models/experiments.py | Experiment.has_running_jobs | def has_running_jobs(self) -> bool:
""""Return a boolean indicating if the experiment has any running jobs"""
return self.jobs.exclude(status__status__in=ExperimentLifeCycle.DONE_STATUS).exists() | python | def has_running_jobs(self) -> bool:
""""Return a boolean indicating if the experiment has any running jobs"""
return self.jobs.exclude(status__status__in=ExperimentLifeCycle.DONE_STATUS).exists() | [
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polyaxon/polyaxon | polyaxon/scopes/authentication/internal.py | get_internal_header | def get_internal_header(request: HttpRequest) -> str:
"""
Return request's 'X_POLYAXON_INTERNAL:' header, as a bytestring.
"""
return get_header(request=request, header_service=conf.get('HEADERS_INTERNAL')) | python | def get_internal_header(request: HttpRequest) -> str:
"""
Return request's 'X_POLYAXON_INTERNAL:' header, as a bytestring.
"""
return get_header(request=request, header_service=conf.get('HEADERS_INTERNAL')) | [
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polyaxon/polyaxon | polyaxon/logs_handlers/tasks/log_sidecars.py | logs_sidecars_experiments | def logs_sidecars_experiments(experiment_name: str,
experiment_uuid: str,
job_uuid: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_experiment_job_log(experimen... | python | def logs_sidecars_experiments(experiment_name: str,
experiment_uuid: str,
job_uuid: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_experiment_job_log(experimen... | [
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polyaxon/polyaxon | polyaxon/logs_handlers/tasks/log_sidecars.py | logs_sidecars_jobs | def logs_sidecars_jobs(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_job_logs(job_uuid=job_uuid,
job_name=job_name,
log_lines=log_lines)
... | python | def logs_sidecars_jobs(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_job_logs(job_uuid=job_uuid,
job_name=job_name,
log_lines=log_lines)
... | [
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polyaxon/polyaxon | polyaxon/logs_handlers/tasks/log_sidecars.py | logs_sidecars_builds | def logs_sidecars_builds(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_build_job_logs(job_uuid=job_uuid,
job_name=job_name,
... | python | def logs_sidecars_builds(job_uuid: str,
job_name: str,
log_lines: Optional[Union[str, Iterable[str]]]) -> None:
"""Signal handling for sidecars logs."""
handle_build_job_logs(job_uuid=job_uuid,
job_name=job_name,
... | [
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polyaxon/polyaxon | polyaxon/db/redis/group_check.py | GroupChecks.is_checked | def is_checked(self) -> bool:
"""One task ran (checked)."""
if not self.redis_key_checked:
return False
value = self._red.get(self.redis_key_checked)
if not value:
return False
return True | python | def is_checked(self) -> bool:
"""One task ran (checked)."""
if not self.redis_key_checked:
return False
value = self._red.get(self.redis_key_checked)
if not value:
return False
return True | [
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polyaxon/polyaxon | polyaxon/db/redis/group_check.py | GroupChecks.is_delayed | def is_delayed(self) -> bool:
"""One task ran (checked), and one task has been delayed."""
if not self.redis_key_delayed:
return False
value = self._red.get(self.redis_key_delayed)
if not value:
return False
return True | python | def is_delayed(self) -> bool:
"""One task ran (checked), and one task has been delayed."""
if not self.redis_key_delayed:
return False
value = self._red.get(self.redis_key_delayed)
if not value:
return False
return True | [
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] | e1724f0756b1a42f9e7aa08a976584a84ef7f016 | https://github.com/polyaxon/polyaxon/blob/e1724f0756b1a42f9e7aa08a976584a84ef7f016/polyaxon/db/redis/group_check.py#L48-L57 | train | Returns True if one task ran and one task has been delayed. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
polyaxon/polyaxon | polyaxon/streams/consumers/consumers.py | Consumer.connect | def connect(self):
"""This method connects to RabbitMQ, returning the connection handle.
When the connection is established, the on_connection_open method
will be invoked by pika.
:rtype: pika.SelectConnection
"""
_logger.info('Connecting to %s', self.AMQP_URL)
w... | python | def connect(self):
"""This method connects to RabbitMQ, returning the connection handle.
When the connection is established, the on_connection_open method
will be invoked by pika.
:rtype: pika.SelectConnection
"""
_logger.info('Connecting to %s', self.AMQP_URL)
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polyaxon/polyaxon | polyaxon/streams/consumers/consumers.py | Consumer.on_channel_open | def on_channel_open(self, channel):
"""This method is invoked by pika when the channel has been opened.
The channel object is passed in so we can make use of it.
Since the channel is now open, we'll declare the exchange to use.
:param pika.channel.Channel channel: The channel object
... | python | def on_channel_open(self, channel):
"""This method is invoked by pika when the channel has been opened.
The channel object is passed in so we can make use of it.
Since the channel is now open, we'll declare the exchange to use.
:param pika.channel.Channel channel: The channel object
... | [
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] | e1724f0756b1a42f9e7aa08a976584a84ef7f016 | https://github.com/polyaxon/polyaxon/blob/e1724f0756b1a42f9e7aa08a976584a84ef7f016/polyaxon/streams/consumers/consumers.py#L121-L132 | train | This method is invoked by pika when the channel is opened. | Pu7Z6IJCgH3a,vcEHXBQXuDuh,sHOWSIAKtU58,ZVWAAMjVVHHl,qRin5pdYOdbB,IySsVMyKT3tF,FwEHNICjJCy0,yISIa0MMKKfB,GAtvbI59wr0o,OmNM6rT0Sgul,gu1MSKhYvigU,S2TTo9DhhiSh,aaLV7ZjAfkcR,ker4pIJmdvxf,WaQEaQCVMQ03,xV97BFGi0hY9,YnM1HtHE4j7G,X5FyJb4ToTo6,jLmadlzMdunT,GGFwFLsDF9Fv,prtR0Uw1GMh5,oNamnshN4dFG,QZzQeAYvsoum,VHAt7CcYKC2T,cKsTbNGL... |
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