max_stars_repo_path stringlengths 4 286 | max_stars_repo_name stringlengths 5 119 | max_stars_count int64 0 191k | id stringlengths 1 7 | content stringlengths 6 1.03M | content_cleaned stringlengths 6 1.03M | language stringclasses 111 values | language_score float64 0.03 1 | comments stringlengths 0 556k | edu_score float64 0.32 5.03 | edu_int_score int64 0 5 |
|---|---|---|---|---|---|---|---|---|---|---|
notebooks/102-BDP-try-timeseries.py | zeou1/maggot_models | 0 | 6620551 | #%%
import pandas as pd
import numpy as np
from graspy.embed import ClassicalMDS
import seaborn as sns
from sklearn.metrics import pairwise_distances
data_loc = "maggot_models/data/external/17-08-26L6-allC-cl.csv"
ts_df = pd.read_csv(data_loc, index_col=None)
ts_mat = ts_df.values.T
# %% [markdown]
# #
corr_mat = pairwise_distances(ts_mat, metric="correlation")
# %% [markdown]
# #
sns.clustermap(corr_mat)
# %% [markdown]
# #
from graspy.plot import pairplot
mds = ClassicalMDS(dissimilarity="precomputed")
embed = mds.fit_transform(corr_mat)
pairplot(embed)
| #%%
import pandas as pd
import numpy as np
from graspy.embed import ClassicalMDS
import seaborn as sns
from sklearn.metrics import pairwise_distances
data_loc = "maggot_models/data/external/17-08-26L6-allC-cl.csv"
ts_df = pd.read_csv(data_loc, index_col=None)
ts_mat = ts_df.values.T
# %% [markdown]
# #
corr_mat = pairwise_distances(ts_mat, metric="correlation")
# %% [markdown]
# #
sns.clustermap(corr_mat)
# %% [markdown]
# #
from graspy.plot import pairplot
mds = ClassicalMDS(dissimilarity="precomputed")
embed = mds.fit_transform(corr_mat)
pairplot(embed)
| en | 0.289781 | #%% # %% [markdown] # # # %% [markdown] # # # %% [markdown] # # | 2.316686 | 2 |
pychron/processing/analyses/view/regression_view.py | ASUPychron/pychron | 31 | 6620552 | # ===============================================================================
# Copyright 2018 ross
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ===============================================================================
from chaco.plot_containers import HPlotContainer
from enable.component_editor import ComponentEditor
from traits.api import HasTraits, Instance, Any
from traitsui.api import View, UItem
from pychron.core.helpers.formatting import format_percent_error, errorfmt
from pychron.graph.stacked_graph import StackedGraph
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
from pychron.graph.tools.regression_inspector import RegressionInspectorTool
from pychron.pychron_constants import PLUSMINUS
class AnalysisRegressionInspectorTool(RegressionInspectorTool):
analysis = Any
def assemble_lines(self):
lines = super(AnalysisRegressionInspectorTool, self).assemble_lines()
an = self.analysis
a = an.age
ef = errorfmt(a, an.age_err)
ef_wo_j = errorfmt(a, an.age_err_wo_j)
lines.insert(0, "Date={:0.4f} {}{} w/o_J={}".format(a, PLUSMINUS, ef, ef_wo_j))
return lines
class AnalysisRegressionGraph(StackedRegressionGraph):
analysis = Any
def regression_inspector_factory(self, line):
tool = AnalysisRegressionInspectorTool(component=line, analysis=self.analysis)
return tool
class RegressionView(HasTraits):
name = "Regressions"
container = Instance(HPlotContainer)
analysis = Any
def initialize(self, an):
an.load_raw_data()
self.analysis = an
self.setup_graph(an)
def setup_graph(self, an):
container = HPlotContainer()
container_dict = {"spacing": 5, "stack_order": "top_to_bottom"}
sg = StackedGraph(container_dict=container_dict)
bg = AnalysisRegressionGraph(container_dict=container_dict, analysis=an)
ig = AnalysisRegressionGraph(container_dict=container_dict, analysis=an)
isos = an.sorted_values(reverse=False)
sisos = [iso for iso in isos if iso.sniff.offset_xs.shape[0]]
for i, iso in enumerate(sisos):
sniff = iso.sniff
p = sg.new_plot(ytitle=iso.name, xtitle="Time (s)", title="Equilibration")
sg.add_axis_tool(p, p.x_axis)
sg.add_axis_tool(p, p.y_axis)
sg.new_series(sniff.offset_xs, sniff.ys, marker="circle", type="scatter")
sg.set_y_limits(pad="0.1", plotid=i)
sg.set_x_limits(min_=0, max_=max(sniff.offset_xs) * 1.05, plotid=i)
iisos = [iso for iso in isos if iso.offset_xs.shape[0]]
baselines = []
for i, iso in enumerate(iisos):
if iso.baseline.offset_xs.shape[0]:
baselines.append(iso.baseline)
p = ig.new_plot(
ytitle="{}({})".format(iso.name, iso.detector),
xtitle="Time (s)",
title="Isotope",
)
ig.add_axis_tool(p, p.x_axis)
ig.add_axis_tool(p, p.y_axis)
ig.new_series(
iso.offset_xs,
iso.ys,
display_filter_bounds=True,
filter_outliers_dict=iso.filter_outliers_dict,
color="blue",
type="scatter",
fit=iso.efit,
)
ig.set_regressor(iso.regressor, i)
ig.set_y_limits(pad="0.1", plotid=i)
ig.set_x_limits(min_=0, max_=max(iso.offset_xs) * 1.05, plotid=i)
ig.refresh()
ig.on_trait_change(self.handle_regression, "regression_results")
for i, baseline in enumerate(baselines):
p = bg.new_plot(
ytitle=baseline.detector, xtitle="Time (s)", title="Baseline"
)
bg.add_axis_tool(p, p.x_axis)
bg.add_axis_tool(p, p.y_axis)
bg.new_series(
baseline.offset_xs,
baseline.ys,
filter_outliers_dict=baseline.filter_outliers_dict,
display_filter_bounds=True,
color="red",
type="scatter",
fit=baseline.efit,
)
bg.set_regressor(baseline.regressor, i)
bg.set_y_limits(pad="0.1", plotid=i)
bg.set_x_limits(pad="0.025", plotid=i)
bg.refresh()
container.add(sg.plotcontainer)
container.add(ig.plotcontainer)
container.add(bg.plotcontainer)
self.container = container
def handle_regression(self, new):
if new:
for plot, regressor in new:
for k, iso in self.analysis.isotopes.items():
yt = plot.y_axis.title
if k == yt or "{}({})".format(iso.name, iso.detector) == yt:
iso.set_fit(regressor.get_fit_dict())
break
self.analysis.calculate_age(force=True)
self.analysis.analysis_view.refresh()
def traits_view(self):
v = View(
UItem("container", style="custom", editor=ComponentEditor()), resizable=True
)
return v
# ============= EOF =============================================
| # ===============================================================================
# Copyright 2018 ross
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ===============================================================================
from chaco.plot_containers import HPlotContainer
from enable.component_editor import ComponentEditor
from traits.api import HasTraits, Instance, Any
from traitsui.api import View, UItem
from pychron.core.helpers.formatting import format_percent_error, errorfmt
from pychron.graph.stacked_graph import StackedGraph
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
from pychron.graph.tools.regression_inspector import RegressionInspectorTool
from pychron.pychron_constants import PLUSMINUS
class AnalysisRegressionInspectorTool(RegressionInspectorTool):
analysis = Any
def assemble_lines(self):
lines = super(AnalysisRegressionInspectorTool, self).assemble_lines()
an = self.analysis
a = an.age
ef = errorfmt(a, an.age_err)
ef_wo_j = errorfmt(a, an.age_err_wo_j)
lines.insert(0, "Date={:0.4f} {}{} w/o_J={}".format(a, PLUSMINUS, ef, ef_wo_j))
return lines
class AnalysisRegressionGraph(StackedRegressionGraph):
analysis = Any
def regression_inspector_factory(self, line):
tool = AnalysisRegressionInspectorTool(component=line, analysis=self.analysis)
return tool
class RegressionView(HasTraits):
name = "Regressions"
container = Instance(HPlotContainer)
analysis = Any
def initialize(self, an):
an.load_raw_data()
self.analysis = an
self.setup_graph(an)
def setup_graph(self, an):
container = HPlotContainer()
container_dict = {"spacing": 5, "stack_order": "top_to_bottom"}
sg = StackedGraph(container_dict=container_dict)
bg = AnalysisRegressionGraph(container_dict=container_dict, analysis=an)
ig = AnalysisRegressionGraph(container_dict=container_dict, analysis=an)
isos = an.sorted_values(reverse=False)
sisos = [iso for iso in isos if iso.sniff.offset_xs.shape[0]]
for i, iso in enumerate(sisos):
sniff = iso.sniff
p = sg.new_plot(ytitle=iso.name, xtitle="Time (s)", title="Equilibration")
sg.add_axis_tool(p, p.x_axis)
sg.add_axis_tool(p, p.y_axis)
sg.new_series(sniff.offset_xs, sniff.ys, marker="circle", type="scatter")
sg.set_y_limits(pad="0.1", plotid=i)
sg.set_x_limits(min_=0, max_=max(sniff.offset_xs) * 1.05, plotid=i)
iisos = [iso for iso in isos if iso.offset_xs.shape[0]]
baselines = []
for i, iso in enumerate(iisos):
if iso.baseline.offset_xs.shape[0]:
baselines.append(iso.baseline)
p = ig.new_plot(
ytitle="{}({})".format(iso.name, iso.detector),
xtitle="Time (s)",
title="Isotope",
)
ig.add_axis_tool(p, p.x_axis)
ig.add_axis_tool(p, p.y_axis)
ig.new_series(
iso.offset_xs,
iso.ys,
display_filter_bounds=True,
filter_outliers_dict=iso.filter_outliers_dict,
color="blue",
type="scatter",
fit=iso.efit,
)
ig.set_regressor(iso.regressor, i)
ig.set_y_limits(pad="0.1", plotid=i)
ig.set_x_limits(min_=0, max_=max(iso.offset_xs) * 1.05, plotid=i)
ig.refresh()
ig.on_trait_change(self.handle_regression, "regression_results")
for i, baseline in enumerate(baselines):
p = bg.new_plot(
ytitle=baseline.detector, xtitle="Time (s)", title="Baseline"
)
bg.add_axis_tool(p, p.x_axis)
bg.add_axis_tool(p, p.y_axis)
bg.new_series(
baseline.offset_xs,
baseline.ys,
filter_outliers_dict=baseline.filter_outliers_dict,
display_filter_bounds=True,
color="red",
type="scatter",
fit=baseline.efit,
)
bg.set_regressor(baseline.regressor, i)
bg.set_y_limits(pad="0.1", plotid=i)
bg.set_x_limits(pad="0.025", plotid=i)
bg.refresh()
container.add(sg.plotcontainer)
container.add(ig.plotcontainer)
container.add(bg.plotcontainer)
self.container = container
def handle_regression(self, new):
if new:
for plot, regressor in new:
for k, iso in self.analysis.isotopes.items():
yt = plot.y_axis.title
if k == yt or "{}({})".format(iso.name, iso.detector) == yt:
iso.set_fit(regressor.get_fit_dict())
break
self.analysis.calculate_age(force=True)
self.analysis.analysis_view.refresh()
def traits_view(self):
v = View(
UItem("container", style="custom", editor=ComponentEditor()), resizable=True
)
return v
# ============= EOF =============================================
| en | 0.748896 | # =============================================================================== # Copyright 2018 ross # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # =============================================================================== # ============= EOF ============================================= | 1.838742 | 2 |
src/connect4.py | ScrypticLabs/iWriter | 0 | 6620553 | <filename>src/connect4.py
"""
An interactive game that is short but fun. This game can be played several times without dedicating too much of your personal time.
It doesn’t require very accurate eye tracking, as selecting what column to place the chip in only requires the x-coordinates.
In general, the selection of the columns is based on gaze and dwell.
"""
from pygame import *
from connect4Images import *
from random import randint
class connect4:
def __init__(self, screen):
"Initializes the class of connect4"
self.screen = screen
self.gameBoard = [['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_']]
self.currentTurn = 1
self.winner = ""
self.backgroundValue = True
self.countBlue = 0
self.countPurple = 0
self.connect4boardRect = Rect(350, 15, 1260, 840)
self.cursor = 0
self.mb = 0
self.dwell_delay = 0
self.maxDelay = 100
def getActivity(self, gazePos, old_gazePos):
"""Gets the user activity of each piece"""
if self.connect4boardRect.collidepoint(gazePos) or ((gazePos[1]-15)//140 < 6 and (gazePos[0]-350)//140 < 9):
if self.dwell_delay < self.maxDelay:
self.dwell_delay += 1
else:
if self.dwell_delay > 0:
self.dwell_delay -= 1
def performAction(self, gazePos, old_gazePos):
"""Sets clicked to True when there is user activity for a certain duration"""
self.getActivity(gazePos, old_gazePos)
if self.dwell_delay == self.maxDelay:
self.mb = 1
self.cursor = gazePos
self.dwell_delay = 0
else:
self.mb = 0
def main(self, cursor, mb):
"Call this in while loop to run all needed components of the game"
if self.backgroundValue == True:
self.screen.blit(background, (0, -400))
self.drawboard()
self.backgroundValue = False
if mb == 1:
self.drawboard()
self.gameplay(cursor, mb)
self.checkwinner()
self.gameover(cursor)
def text(self, screen, text, size, color, location):
"Used to display text on the screen"
screen.blit(font.Font("Fonts/HelveticaNeue-Light.otf", size).render(str(text), True, color), location)
def drawboard(self):
"Draws the connect4 board and the chips on the screen"
cover = Surface((1920, 1080), SRCALPHA)
self.screen.blit(board, (350, 15))
for x in range(9):
for y in range(6):
if self.gameBoard[y][x] == "B":
draw.circle(cover, (35, 107, 172, 230), (420+(x*140), 85+(y*140)), 60)
elif self.gameBoard[y][x] == "P":
draw.circle(cover, (123, 43, 157, 230), (420+(x*140), 85+(y*140)), 60)
self.screen.blit(cover, (0, 0))
def gameplay(self, cursor, mb):
"This function does the move for the artificial inteeligence and also display the user and artififcial intelligences move"
if self.currentTurn == 1:
clickX = (cursor[0]-350)//140
if self.currentTurn == 2:
clickX = randint(0, 8)
for y in range(0, 6):
if self.gameBoard[y][clickX] != "_":
break
elif self.gameBoard[y][clickX] == "_":
if self.currentTurn == 1:
self.gameBoard[y][clickX] = "B"
elif self.currentTurn == 2:
self.gameBoard[y][clickX] = "P"
self.gameBoard[y-1][clickX] = "_"
self.drawboard()
display.flip()
for row in self.gameBoard:
self.countBlue += row.count("B")
self.countPurple += row.count("P")
if self.currentTurn == 1:
if (self.countBlue - self.countPurple) == 1:
self.currentTurn = 2
elif self.currentTurn == 2:
if (self.countPurple - self.countBlue) == 0:
self.currentTurn = 1
self.countBlue = 0
self.countPurple = 0
def checkwinner(self):
"Checks to see if any of the players have won. if yes which one"
for y in range(6):
for x in range(9):
if self.gameBoard[y][x] != "_":
if x < 6 and y < 3:
if self.gameBoard[y][x] == self.gameBoard[y+1][x+1] == self.gameBoard[y+2][x+2] == self.gameBoard[y+3][y+3]:
self.winner = self.gameBoard[y][x]
if x < 6:
if self.gameBoard[y][x] == self.gameBoard[y][x+1] == self.gameBoard[y][x+2] == self.gameBoard[y][x+3]:
self.winner = self.gameBoard[y][x]
if y < 3:
if self.gameBoard[y][x] == self.gameBoard[y+1][x] == self.gameBoard[y+2][x] == self.gameBoard[y+3][x]:
self.winner = self.gameBoard[y][x]
def gameover(self, cursor):
"Displays the gameover screen and the user gets to chose whether or not they want to play again"
if self.winner != "":
cover = Surface((1260, 840), SRCALPHA)
draw.rect(cover, (0, 0, 0, 225), (0, 0, 1260, 840))
self.screen.blit(cover, (350, 15))
if self.winner == "P":
self.text(self.screen, "Purple Won", 160, (255, 255, 255), (640, 30))
if self.winner == "B":
self.text(self.screen, "Blue Won", 160, (255, 255, 255), (645, 30))
self.screen.blit(button, (810, 300))
self.text(self.screen, "Play Again", 60, (255, 255, 255), (850, 315))
againRect = Rect(825, 315, 320, 80)
if againRect.collidepoint(cursor):
connect4.__init__(self, self.screen)
| <filename>src/connect4.py
"""
An interactive game that is short but fun. This game can be played several times without dedicating too much of your personal time.
It doesn’t require very accurate eye tracking, as selecting what column to place the chip in only requires the x-coordinates.
In general, the selection of the columns is based on gaze and dwell.
"""
from pygame import *
from connect4Images import *
from random import randint
class connect4:
def __init__(self, screen):
"Initializes the class of connect4"
self.screen = screen
self.gameBoard = [['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_'],
['_', '_', '_', '_', '_', '_', '_', '_', '_']]
self.currentTurn = 1
self.winner = ""
self.backgroundValue = True
self.countBlue = 0
self.countPurple = 0
self.connect4boardRect = Rect(350, 15, 1260, 840)
self.cursor = 0
self.mb = 0
self.dwell_delay = 0
self.maxDelay = 100
def getActivity(self, gazePos, old_gazePos):
"""Gets the user activity of each piece"""
if self.connect4boardRect.collidepoint(gazePos) or ((gazePos[1]-15)//140 < 6 and (gazePos[0]-350)//140 < 9):
if self.dwell_delay < self.maxDelay:
self.dwell_delay += 1
else:
if self.dwell_delay > 0:
self.dwell_delay -= 1
def performAction(self, gazePos, old_gazePos):
"""Sets clicked to True when there is user activity for a certain duration"""
self.getActivity(gazePos, old_gazePos)
if self.dwell_delay == self.maxDelay:
self.mb = 1
self.cursor = gazePos
self.dwell_delay = 0
else:
self.mb = 0
def main(self, cursor, mb):
"Call this in while loop to run all needed components of the game"
if self.backgroundValue == True:
self.screen.blit(background, (0, -400))
self.drawboard()
self.backgroundValue = False
if mb == 1:
self.drawboard()
self.gameplay(cursor, mb)
self.checkwinner()
self.gameover(cursor)
def text(self, screen, text, size, color, location):
"Used to display text on the screen"
screen.blit(font.Font("Fonts/HelveticaNeue-Light.otf", size).render(str(text), True, color), location)
def drawboard(self):
"Draws the connect4 board and the chips on the screen"
cover = Surface((1920, 1080), SRCALPHA)
self.screen.blit(board, (350, 15))
for x in range(9):
for y in range(6):
if self.gameBoard[y][x] == "B":
draw.circle(cover, (35, 107, 172, 230), (420+(x*140), 85+(y*140)), 60)
elif self.gameBoard[y][x] == "P":
draw.circle(cover, (123, 43, 157, 230), (420+(x*140), 85+(y*140)), 60)
self.screen.blit(cover, (0, 0))
def gameplay(self, cursor, mb):
"This function does the move for the artificial inteeligence and also display the user and artififcial intelligences move"
if self.currentTurn == 1:
clickX = (cursor[0]-350)//140
if self.currentTurn == 2:
clickX = randint(0, 8)
for y in range(0, 6):
if self.gameBoard[y][clickX] != "_":
break
elif self.gameBoard[y][clickX] == "_":
if self.currentTurn == 1:
self.gameBoard[y][clickX] = "B"
elif self.currentTurn == 2:
self.gameBoard[y][clickX] = "P"
self.gameBoard[y-1][clickX] = "_"
self.drawboard()
display.flip()
for row in self.gameBoard:
self.countBlue += row.count("B")
self.countPurple += row.count("P")
if self.currentTurn == 1:
if (self.countBlue - self.countPurple) == 1:
self.currentTurn = 2
elif self.currentTurn == 2:
if (self.countPurple - self.countBlue) == 0:
self.currentTurn = 1
self.countBlue = 0
self.countPurple = 0
def checkwinner(self):
"Checks to see if any of the players have won. if yes which one"
for y in range(6):
for x in range(9):
if self.gameBoard[y][x] != "_":
if x < 6 and y < 3:
if self.gameBoard[y][x] == self.gameBoard[y+1][x+1] == self.gameBoard[y+2][x+2] == self.gameBoard[y+3][y+3]:
self.winner = self.gameBoard[y][x]
if x < 6:
if self.gameBoard[y][x] == self.gameBoard[y][x+1] == self.gameBoard[y][x+2] == self.gameBoard[y][x+3]:
self.winner = self.gameBoard[y][x]
if y < 3:
if self.gameBoard[y][x] == self.gameBoard[y+1][x] == self.gameBoard[y+2][x] == self.gameBoard[y+3][x]:
self.winner = self.gameBoard[y][x]
def gameover(self, cursor):
"Displays the gameover screen and the user gets to chose whether or not they want to play again"
if self.winner != "":
cover = Surface((1260, 840), SRCALPHA)
draw.rect(cover, (0, 0, 0, 225), (0, 0, 1260, 840))
self.screen.blit(cover, (350, 15))
if self.winner == "P":
self.text(self.screen, "Purple Won", 160, (255, 255, 255), (640, 30))
if self.winner == "B":
self.text(self.screen, "Blue Won", 160, (255, 255, 255), (645, 30))
self.screen.blit(button, (810, 300))
self.text(self.screen, "Play Again", 60, (255, 255, 255), (850, 315))
againRect = Rect(825, 315, 320, 80)
if againRect.collidepoint(cursor):
connect4.__init__(self, self.screen)
| en | 0.96475 | An interactive game that is short but fun. This game can be played several times without dedicating too much of your personal time. It doesn’t require very accurate eye tracking, as selecting what column to place the chip in only requires the x-coordinates. In general, the selection of the columns is based on gaze and dwell. Gets the user activity of each piece Sets clicked to True when there is user activity for a certain duration | 3.576135 | 4 |
hummingbot/strategy/discovery/discovery_market_pair.py | TritumDigitalAssets/hummingbot | 2 | 6620554 | #!/usr/bin/env python
from typing import (
NamedTuple,
Awaitable
)
import pandas as pd
from hummingbot.market.market_base import MarketBase
class DiscoveryMarketPair(NamedTuple):
"""
Specifies a pair of markets for discovery
"""
market_1: MarketBase
market_1_fetch_market_info: Awaitable[pd.DataFrame]
market_2: MarketBase
market_2_fetch_market_info: Awaitable[pd.DataFrame]
def __repr__(self) -> str:
return f"DiscoveryMarketPair({self.market_1.name}, {self.market_2.name})"
| #!/usr/bin/env python
from typing import (
NamedTuple,
Awaitable
)
import pandas as pd
from hummingbot.market.market_base import MarketBase
class DiscoveryMarketPair(NamedTuple):
"""
Specifies a pair of markets for discovery
"""
market_1: MarketBase
market_1_fetch_market_info: Awaitable[pd.DataFrame]
market_2: MarketBase
market_2_fetch_market_info: Awaitable[pd.DataFrame]
def __repr__(self) -> str:
return f"DiscoveryMarketPair({self.market_1.name}, {self.market_2.name})"
| en | 0.474411 | #!/usr/bin/env python Specifies a pair of markets for discovery | 2.725059 | 3 |
projecteuler/9.py | m00nb0w/oghma | 0 | 6620555 | <reponame>m00nb0w/oghma
#!/bin/python3
import sys
t = int(input().strip())
for a0 in range(t):
n = int(input().strip())
res = -1
for a in range(1, n // 3 + 1):
b = (n - (a * n) / (n - a)) / 2
if (int(b) == b):
b = int(b)
c = n - a - b
if a < b and b < c:
res = max(res, a * b * c)
print(res)
| #!/bin/python3
import sys
t = int(input().strip())
for a0 in range(t):
n = int(input().strip())
res = -1
for a in range(1, n // 3 + 1):
b = (n - (a * n) / (n - a)) / 2
if (int(b) == b):
b = int(b)
c = n - a - b
if a < b and b < c:
res = max(res, a * b * c)
print(res) | ru | 0.16812 | #!/bin/python3 | 2.895765 | 3 |
sk.py | zeroby0/lms-stalker | 1 | 6620556 | #!/usr/bin/env python
from __future__ import print_function
# https://github.com/zeroby0/lms-stalker
# <NAME>
import requests
from bs4 import BeautifulSoup
import warnings
import datetime, time, os, json
warnings.filterwarnings("ignore")
class stlk:
def pack_db(self): # too lazy to find python commands
os.system("cat " + self.DB_FILE + " | python -mjson.tool > ./public/db.pack.json")
os.system("cd ./public && zip db.pack.json.zip db.pack.json") # cd ing to avoid unpacking to folder
os.system("cd ./public && tar -czf db.pack.json.tar.gz db.pack.json")
# os.system("cp -r ./public/. /var/www/stalk/") # serving files with nginx
def set_db(self):
with open( self.DB_FILE, 'w') as f:
json.dump( self.DB , f)
def get_db(self):
with open( self.DB_FILE ) as dbase_file:
dbase = json.load(dbase_file)
return dbase
def create_db(self):
if not os.path.exists( self.DB_FILE ):
template = {}
with open( self.DB_FILE, 'w') as f:
json.dump(template, f)
def __init__(self,username, password,DB_FILE = "./db.json"):
self.username = username
self.password = password
self.DB_FILE = DB_FILE
self.create_db()
self.DB = self.get_db()
def log_user(self, id):
if not self.DB.has_key(id):
self.DB[id] = {"time_array": []}
self.DB[id]["time_array"].append( "{:%d %m, %Y, %H %M %S}".format(datetime.datetime.now()) )
def scan(self):
payload = {
'username': self.username,
'password': self.password
}
self.DB["0nline"] = [{"Last checked at" : "{:%d %m, %Y, %H %M %S}".format(datetime.datetime.now()) }]
with requests.Session() as s:
p = s.post('https://lms.iiitb.ac.in/moodle/login/index.php', data=payload,verify=False)
r = s.get('https://lms.iiitb.ac.in/moodle/my/',verify=False)
soup=BeautifulSoup(r.text)
g_data=soup.find_all("div",{"class":"user"})
print("\n[")
for i in g_data:
if i.text in [ "imt2015524 <NAME>"]: continue # Put your ID here
print(" " + i.text + ",")
self.log_user(i.text)
self.DB["0nline"].append(i.text)
self.set_db()
# self.pack_db()
# current_list[i.text] = datetime.datetime.now()
# ,i.find_all("a")[0]['title'] // for time
def stalk(self):
while True:
try:
self.scan()
print("]")
self.pack_db()
print("____________________________________________________");
time.sleep(60)
except:
print("Error occured, retrying")
stk = stlk("Roll Number", "Password")
stk.stalk()
| #!/usr/bin/env python
from __future__ import print_function
# https://github.com/zeroby0/lms-stalker
# <NAME>
import requests
from bs4 import BeautifulSoup
import warnings
import datetime, time, os, json
warnings.filterwarnings("ignore")
class stlk:
def pack_db(self): # too lazy to find python commands
os.system("cat " + self.DB_FILE + " | python -mjson.tool > ./public/db.pack.json")
os.system("cd ./public && zip db.pack.json.zip db.pack.json") # cd ing to avoid unpacking to folder
os.system("cd ./public && tar -czf db.pack.json.tar.gz db.pack.json")
# os.system("cp -r ./public/. /var/www/stalk/") # serving files with nginx
def set_db(self):
with open( self.DB_FILE, 'w') as f:
json.dump( self.DB , f)
def get_db(self):
with open( self.DB_FILE ) as dbase_file:
dbase = json.load(dbase_file)
return dbase
def create_db(self):
if not os.path.exists( self.DB_FILE ):
template = {}
with open( self.DB_FILE, 'w') as f:
json.dump(template, f)
def __init__(self,username, password,DB_FILE = "./db.json"):
self.username = username
self.password = password
self.DB_FILE = DB_FILE
self.create_db()
self.DB = self.get_db()
def log_user(self, id):
if not self.DB.has_key(id):
self.DB[id] = {"time_array": []}
self.DB[id]["time_array"].append( "{:%d %m, %Y, %H %M %S}".format(datetime.datetime.now()) )
def scan(self):
payload = {
'username': self.username,
'password': self.password
}
self.DB["0nline"] = [{"Last checked at" : "{:%d %m, %Y, %H %M %S}".format(datetime.datetime.now()) }]
with requests.Session() as s:
p = s.post('https://lms.iiitb.ac.in/moodle/login/index.php', data=payload,verify=False)
r = s.get('https://lms.iiitb.ac.in/moodle/my/',verify=False)
soup=BeautifulSoup(r.text)
g_data=soup.find_all("div",{"class":"user"})
print("\n[")
for i in g_data:
if i.text in [ "imt2015524 <NAME>"]: continue # Put your ID here
print(" " + i.text + ",")
self.log_user(i.text)
self.DB["0nline"].append(i.text)
self.set_db()
# self.pack_db()
# current_list[i.text] = datetime.datetime.now()
# ,i.find_all("a")[0]['title'] // for time
def stalk(self):
while True:
try:
self.scan()
print("]")
self.pack_db()
print("____________________________________________________");
time.sleep(60)
except:
print("Error occured, retrying")
stk = stlk("Roll Number", "Password")
stk.stalk()
| en | 0.509616 | #!/usr/bin/env python # https://github.com/zeroby0/lms-stalker # <NAME> # too lazy to find python commands # cd ing to avoid unpacking to folder # os.system("cp -r ./public/. /var/www/stalk/") # serving files with nginx # Put your ID here # self.pack_db() # current_list[i.text] = datetime.datetime.now() # ,i.find_all("a")[0]['title'] // for time | 2.337272 | 2 |
edmunds/gae/gaetestcase.py | LowieHuyghe/edmunds-python | 4 | 6620557 |
from edmunds.foundation.testing.testcase import TestCase
import sys
def gae_can_run():
return sys.version_info < (3, 0)
if gae_can_run():
from google.appengine.ext import testbed
class GaeTestCase(TestCase):
@staticmethod
def can_run():
"""
Check if can run test
:return: Boolean
"""
return gae_can_run()
def set_up(self):
"""
Set up the test case
"""
if not self.can_run():
self.skip("Google Cloud SDK doesn't run in Python 3+")
self.testbed = testbed.Testbed()
self.testbed.activate()
super(GaeTestCase, self).set_up()
def tear_down(self):
"""
Tear down the test case
"""
super(GaeTestCase, self).tear_down()
try:
self.testbed.deactivate()
except testbed.NotActivatedError:
pass
|
from edmunds.foundation.testing.testcase import TestCase
import sys
def gae_can_run():
return sys.version_info < (3, 0)
if gae_can_run():
from google.appengine.ext import testbed
class GaeTestCase(TestCase):
@staticmethod
def can_run():
"""
Check if can run test
:return: Boolean
"""
return gae_can_run()
def set_up(self):
"""
Set up the test case
"""
if not self.can_run():
self.skip("Google Cloud SDK doesn't run in Python 3+")
self.testbed = testbed.Testbed()
self.testbed.activate()
super(GaeTestCase, self).set_up()
def tear_down(self):
"""
Tear down the test case
"""
super(GaeTestCase, self).tear_down()
try:
self.testbed.deactivate()
except testbed.NotActivatedError:
pass
| en | 0.383316 | Check if can run test :return: Boolean Set up the test case Tear down the test case | 2.420376 | 2 |
corehq/apps/app_manager/translations.py | bglar/commcare-hq | 1 | 6620558 | from lxml import etree
import copy
from openpyxl.shared.exc import InvalidFileException
from corehq.apps.app_manager.exceptions import (
FormNotFoundException,
ModuleNotFoundException,
)
from corehq.apps.app_manager.util import save_xform
from corehq.apps.app_manager.xform import namespaces, WrappedNode
from dimagi.utils.excel import WorkbookJSONReader, HeaderValueError
from django.contrib import messages
from django.utils.translation import ugettext as _
def process_bulk_app_translation_upload(app, f):
"""
Process the bulk upload file for the given app.
We return these message tuples instead of calling them now to allow this
function to be used independently of request objects.
:param app:
:param f:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
def none_or_unicode(val):
return unicode(val) if val is not None else val
msgs = []
headers = expected_bulk_app_sheet_headers(app)
expected_sheets = {h[0]: h[1] for h in headers}
processed_sheets = set()
try:
workbook = WorkbookJSONReader(f)
except (HeaderValueError, InvalidFileException) as e:
msgs.append(
(messages.error, _("App Translation Failed! " + str(e)))
)
return msgs
for sheet in workbook.worksheets:
# sheet.__iter__ can only be called once, so cache the result
rows = [row for row in sheet]
# Convert every key and value to a string
for i in xrange(len(rows)):
rows[i] = {unicode(k): none_or_unicode(v) for k, v in rows[i].iteritems()}
# CHECK FOR REPEAT SHEET
if sheet.worksheet.title in processed_sheets:
msgs.append((
messages.error,
'Sheet "%s" was repeated. Only the first ' +
'occurrence has been processed' %
sheet.worksheet.title
))
continue
# CHECK FOR BAD SHEET NAME
expected_columns = expected_sheets.get(sheet.worksheet.title, None)
if expected_columns is None:
msgs.append((
messages.error,
'Skipping sheet "%s", did not recognize title' %
sheet.worksheet.title
))
continue
# CHECK FOR MISSING KEY COLUMN
if sheet.worksheet.title == "Modules and Forms":
# Several columns on this sheet could be used to uniquely identify
# rows. Using sheet_name for now, but unique_id could also be used.
if expected_columns[1] not in sheet.headers:
msgs.append((
messages.error,
'Skipping sheet "%s", could not find "%s" column' %
(sheet.worksheet.title, expected_columns[1])
))
continue
elif expected_columns[0] == "case_property":
# It's a module sheet
if (expected_columns[0] not in sheet.headers
or expected_columns[1] not in sheet.headers):
msgs.append((
messages.error,
'Skipping sheet "%s", could not find case_property'
' or list_or_detail column.' % sheet.worksheet.title
))
continue
else:
# It's a form sheet
if expected_columns[0] not in sheet.headers:
msgs.append((
messages.error,
'Skipping sheet "%s", could not find label column' %
sheet.worksheet.title
))
continue
processed_sheets.add(sheet.worksheet.title)
# CHECK FOR MISSING COLUMNS
missing_cols = set(expected_columns) - set(sheet.headers)
if len(missing_cols) > 0:
msgs.append((
messages.warning,
'Sheet "%s" has less columns than expected. '
'Sheet will be processed but the following'
' translations will be unchanged: %s'
% (sheet.worksheet.title, " ,".join(missing_cols))
))
# CHECK FOR EXTRA COLUMNS
extra_cols = set(sheet.headers) - set(expected_columns)
if len(extra_cols) > 0:
msgs.append((
messages.warning,
'Sheet "%s" has unrecognized columns. '
'Sheet will be processed but ignoring the following columns: %s'
% (sheet.worksheet.title, " ,".join(extra_cols))
))
# NOTE: At the moment there is no missing row detection.
# This could be added if we want though
# (it is not that bad if a user leaves out a row)
if sheet.worksheet.title == "Modules_and_forms":
# It's the first sheet
ms = process_modules_and_forms_sheet(rows, app)
msgs.extend(ms)
elif sheet.headers[0] == "case_property":
# It's a module sheet
ms = update_case_list_translations(sheet, rows, app)
msgs.extend(ms)
else:
# It's a form sheet
ms = update_form_translations(sheet, rows, missing_cols, app)
msgs.extend(ms)
msgs.append(
(messages.success, _("App Translations Updated!"))
)
return msgs
def expected_bulk_app_sheet_headers(app):
'''
Returns lists representing the expected structure of bulk app translation
excel file uploads.
The list will be in the form:
[
["sheetname", ["column name1", "column name 2"]],
["sheet2 name", [...]],
...
]
:param app:
:return:
'''
languages_list = ['default_' + l for l in app.langs]
audio_lang_list = ['audio_' + l for l in app.langs]
image_lang_list = ['image_' + l for l in app.langs]
video_lang_list = ['video_' + l for l in app.langs]
headers = []
# Add headers for the first sheet
headers.append(
["Modules_and_forms",
['Type', 'sheet_name'] + languages_list +
['label_for_cases_%s' % l for l in app.langs] +
['icon_filepath', 'audio_filepath', 'unique_id']]
)
for mod_index, module in enumerate(app.get_modules()):
module_string = "module" + str(mod_index + 1)
headers.append([module_string, ['case_property', 'list_or_detail'] + languages_list])
for form_index, form in enumerate(module.get_forms()):
form_string = module_string + "_form" + str(form_index + 1)
headers.append([
form_string,
["label"] + languages_list + audio_lang_list + image_lang_list
+ video_lang_list
])
return headers
def process_modules_and_forms_sheet(rows, app):
"""
Modify the translations and media references for the modules and forms in
the given app as per the data provided in rows.
This does not save the changes to the database.
:param rows:
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
msgs = []
for row in rows:
identifying_text = row.get('sheet_name', '').split('_')
if len(identifying_text) not in (1, 2):
msgs.append((
messages.error,
'Invalid sheet_name "%s", skipping row.' % row.get(
'sheet_name', ''
)
))
continue
module_index = int(identifying_text[0].replace("module", "")) - 1
try:
document = app.get_module(module_index)
except ModuleNotFoundException:
msgs.append((
messages.error,
'Invalid module in row "%s", skipping row.' % row.get(
'sheet_name'
)
))
continue
if len(identifying_text) == 2:
form_index = int(identifying_text[1].replace("form", "")) - 1
try:
document = document.get_form(form_index)
except FormNotFoundException:
msgs.append((
messages.error,
'Invalid form in row "%s", skipping row.' % row.get(
'sheet_name'
)
))
continue
for lang in app.langs:
translation = row['default_%s' % lang]
if translation:
document.name[lang] = translation
else:
if lang in document.name:
del document.name[lang]
if (has_at_least_one_translation(row, 'label_for_cases', app.langs)
and hasattr(document, 'case_label')):
for lang in app.langs:
translation = row['label_for_cases_%s' % lang]
if translation:
document.case_label[lang] = translation
else:
if lang in document.case_label:
del document.case_label[lang]
image = row.get('icon_filepath', None)
audio = row.get('audio_filepath', None)
if image == '':
image = None
if audio == '':
audio = None
document.media_image = image
document.media_audio = audio
return msgs
def update_form_translations(sheet, rows, missing_cols, app):
"""
Modify the translations of a form given a sheet of translation data.
This does not save the changes to the DB.
:param sheet: a WorksheetJSONReader
:param rows: The rows of the sheet (we can't get this from the sheet
because sheet.__iter__ can only be called once)
:param missing_cols:
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
msgs = []
mod_text, form_text = sheet.worksheet.title.split("_")
module_index = int(mod_text.replace("module", "")) - 1
form_index = int(form_text.replace("form", "")) - 1
form = app.get_module(module_index).get_form(form_index)
if form.source:
xform = form.wrapped_xform()
else:
# This Form doesn't have an xform yet. It is empty.
# Tell the user this?
return msgs
itext = xform.itext_node
assert(itext.exists())
# Make language nodes for each language if they don't yet exist
#
# Currently operating under the assumption that every xForm has at least
# one translation element, that each translation element has a text node
# for each question and that each text node has a value node under it
template_translation_el = None
# Get a translation element to be used as a template for new elements
for lang in app.langs:
trans_el = itext.find("./{f}translation[@lang='%s']" % lang)
if trans_el.exists():
template_translation_el = trans_el
assert(template_translation_el is not None)
# Add missing translation elements
for lang in app.langs:
trans_el = itext.find("./{f}translation[@lang='%s']" % lang)
if not trans_el.exists():
new_trans_el = copy.deepcopy(template_translation_el.xml)
new_trans_el.set('lang', lang)
if lang != app.langs[0]:
# If the language isn't the default language
new_trans_el.attrib.pop('default', None)
else:
new_trans_el.set('default', '')
itext.xml.append(new_trans_el)
# Update the translations
for lang in app.langs:
translation_node = itext.find("./{f}translation[@lang='%s']" % lang)
assert(translation_node.exists())
for row in rows:
label_id = row['label']
text_node = translation_node.find("./{f}text[@id='%s']" % label_id)
if not text_node.exists():
msgs.append((
messages.warning,
"Unrecognized translation label {0} in sheet {1}. That row"
" has been skipped". format(label_id, sheet.worksheet.title)
))
continue
# Add or remove translations
for trans_type in ['default', 'audio', 'image', 'video']:
if trans_type == 'default':
attributes = None
value_node = next(
n for n in text_node.findall("./{f}value")
if 'form' not in n.attrib
)
else:
attributes = {'form': trans_type}
value_node = text_node.find(
"./{f}value[@form='%s']" % trans_type
)
col_key = get_col_key(trans_type, lang)
new_translation = row[col_key]
if not new_translation and col_key not in missing_cols:
# If the cell corresponding to the label for this question
# in this language is empty, fall back to another language
for l in app.langs:
fallback = row[get_col_key(trans_type, l)]
if fallback:
new_translation = fallback
break
if new_translation:
# Create the node if it does not already exist
if not value_node.exists():
e = etree.Element(
"{f}value".format(**namespaces), attributes
)
text_node.xml.append(e)
value_node = WrappedNode(e)
# Update the translation
value_node.xml.text = new_translation
else:
# Remove the node if it already exists
if value_node.exists():
value_node.xml.getparent().remove(value_node.xml)
save_xform(app, form, etree.tostring(xform.xml, encoding="unicode"))
return msgs
def update_case_list_translations(sheet, rows, app):
"""
Modify the translations of a module case list and detail display properties
given a sheet of translation data. The properties in the sheet must be in
the exact same order that they appear in the bulk app translation download.
This function does not save the modified app to the database.
:param sheet:
:param rows: The rows of the sheet (we can't get this from the sheet
because sheet.__iter__ can only be called once)
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
# The list might contain DetailColumn instances in them that have exactly
# the same attributes (but are in different positions). Therefore we must
# match sheet rows to DetailColumns by position.
msgs = []
module_index = int(sheet.worksheet.title.replace("module", "")) - 1
module = app.get_module(module_index)
# It is easier to process the translations if mapping rows are nested under
# their respective DetailColumns
condensed_rows = []
i = 0
while i < len(rows):
if rows[i]['case_property'].endswith(" (ID Mapping Text)"):
# Cut off the id mapping text
rows[i]['case_property'] = rows[i]['case_property'].split(" ")[0]
# Construct a list of mapping rows
mappings = []
j = 1
while (i + j < len(rows) and
rows[i + j]['case_property'].endswith(" (ID Mapping Value)")):
# Cut off the id mapping value part
rows[i + j]['case_property'] = \
rows[i + j]['case_property'].split(" ")[0]
mappings.append(rows[i + j])
j += 1
rows[i]['mappings'] = mappings
condensed_rows.append(rows[i])
i += j
else:
condensed_rows.append(rows[i])
i += 1
list_rows = [
row for row in condensed_rows if row['list_or_detail'] == 'list'
]
detail_rows = [
row for row in condensed_rows if row['list_or_detail'] == 'detail'
]
short_details = list(module.case_details.short.get_columns())
long_details = list(module.case_details.long.get_columns())
# Check length of lists
for expected_list, received_list, word in [
(short_details, list_rows, "list"),
(long_details, detail_rows, "detail")
]:
if len(expected_list) != len(received_list):
msgs.append((
messages.error,
"Expected {0} case {3} properties in sheet {2}, found {1}. "
"No case list or detail properties for sheet {2} were "
"updated".format(
len(expected_list),
len(received_list),
sheet.worksheet.title,
word
)
))
if msgs:
return msgs
# Update the translations
for row, detail in \
zip(list_rows, short_details) + zip(detail_rows, long_details):
# Check that names match (user is not allowed to change property in the
# upload). Mismatched names indicate the user probably botched the sheet.
if row.get('case_property', None) != detail.field:
msgs.append((
messages.error,
'A row in sheet {sheet} has an unexpected value of "{field}" '
'in the case_property column. Case properties must appear in '
'the same order as they do in the bulk app translation '
'download. No translations updated for this row.'.format(
sheet=sheet.worksheet.title,
field=row.get('case_property', "")
)
))
continue
# The logic for updating a mapping and updating a MappingItem and a
# DetailColumn is almost the same. So, we smush the two together.
for index, translation_row in enumerate([row] + row.get("mappings", [])):
ok_to_delete_translations = has_at_least_one_translation(
translation_row, 'default', app.langs)
if ok_to_delete_translations:
for lang in app.langs:
translation = translation_row['default_%s' % lang]
if index == 0:
# For DetailColumns
language_dict = detail.header
else:
# For MappingItems
language_dict = detail['enum'][index - 1].value
if translation:
language_dict[lang] = translation
else:
if lang in language_dict:
del language_dict[lang]
else:
msgs.append((
messages.error,
"You must provide at least one translation" +
" of the case property '%s'" %
translation_row['case_property'] + " (ID Mapping Value)"
if index != 0 else ""
))
return msgs
def has_at_least_one_translation(row, prefix, langs):
"""
Returns true if the given row has at least one translation.
>>> has_at_least_one_translation(
{'default_en': 'Name', 'case_property': 'name'}, 'default', ['en', 'fra']
)
true
>>> has_at_least_one_translation(
{'case_property': 'name'}, 'default', ['en', 'fra']
)
false
:param row:
:param prefix:
:param langs:
:return:
"""
return bool(filter(None, [row[prefix + '_' + l] for l in langs]))
def get_col_key(translation_type, language):
'''
Returns the name of the column in the bulk app translation spreadsheet
given the translation type and language
:param translation_type: What is being translated, i.e. 'default'
or 'image'
:param language:
:return:
'''
return "%s_%s" % (translation_type, language)
| from lxml import etree
import copy
from openpyxl.shared.exc import InvalidFileException
from corehq.apps.app_manager.exceptions import (
FormNotFoundException,
ModuleNotFoundException,
)
from corehq.apps.app_manager.util import save_xform
from corehq.apps.app_manager.xform import namespaces, WrappedNode
from dimagi.utils.excel import WorkbookJSONReader, HeaderValueError
from django.contrib import messages
from django.utils.translation import ugettext as _
def process_bulk_app_translation_upload(app, f):
"""
Process the bulk upload file for the given app.
We return these message tuples instead of calling them now to allow this
function to be used independently of request objects.
:param app:
:param f:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
def none_or_unicode(val):
return unicode(val) if val is not None else val
msgs = []
headers = expected_bulk_app_sheet_headers(app)
expected_sheets = {h[0]: h[1] for h in headers}
processed_sheets = set()
try:
workbook = WorkbookJSONReader(f)
except (HeaderValueError, InvalidFileException) as e:
msgs.append(
(messages.error, _("App Translation Failed! " + str(e)))
)
return msgs
for sheet in workbook.worksheets:
# sheet.__iter__ can only be called once, so cache the result
rows = [row for row in sheet]
# Convert every key and value to a string
for i in xrange(len(rows)):
rows[i] = {unicode(k): none_or_unicode(v) for k, v in rows[i].iteritems()}
# CHECK FOR REPEAT SHEET
if sheet.worksheet.title in processed_sheets:
msgs.append((
messages.error,
'Sheet "%s" was repeated. Only the first ' +
'occurrence has been processed' %
sheet.worksheet.title
))
continue
# CHECK FOR BAD SHEET NAME
expected_columns = expected_sheets.get(sheet.worksheet.title, None)
if expected_columns is None:
msgs.append((
messages.error,
'Skipping sheet "%s", did not recognize title' %
sheet.worksheet.title
))
continue
# CHECK FOR MISSING KEY COLUMN
if sheet.worksheet.title == "Modules and Forms":
# Several columns on this sheet could be used to uniquely identify
# rows. Using sheet_name for now, but unique_id could also be used.
if expected_columns[1] not in sheet.headers:
msgs.append((
messages.error,
'Skipping sheet "%s", could not find "%s" column' %
(sheet.worksheet.title, expected_columns[1])
))
continue
elif expected_columns[0] == "case_property":
# It's a module sheet
if (expected_columns[0] not in sheet.headers
or expected_columns[1] not in sheet.headers):
msgs.append((
messages.error,
'Skipping sheet "%s", could not find case_property'
' or list_or_detail column.' % sheet.worksheet.title
))
continue
else:
# It's a form sheet
if expected_columns[0] not in sheet.headers:
msgs.append((
messages.error,
'Skipping sheet "%s", could not find label column' %
sheet.worksheet.title
))
continue
processed_sheets.add(sheet.worksheet.title)
# CHECK FOR MISSING COLUMNS
missing_cols = set(expected_columns) - set(sheet.headers)
if len(missing_cols) > 0:
msgs.append((
messages.warning,
'Sheet "%s" has less columns than expected. '
'Sheet will be processed but the following'
' translations will be unchanged: %s'
% (sheet.worksheet.title, " ,".join(missing_cols))
))
# CHECK FOR EXTRA COLUMNS
extra_cols = set(sheet.headers) - set(expected_columns)
if len(extra_cols) > 0:
msgs.append((
messages.warning,
'Sheet "%s" has unrecognized columns. '
'Sheet will be processed but ignoring the following columns: %s'
% (sheet.worksheet.title, " ,".join(extra_cols))
))
# NOTE: At the moment there is no missing row detection.
# This could be added if we want though
# (it is not that bad if a user leaves out a row)
if sheet.worksheet.title == "Modules_and_forms":
# It's the first sheet
ms = process_modules_and_forms_sheet(rows, app)
msgs.extend(ms)
elif sheet.headers[0] == "case_property":
# It's a module sheet
ms = update_case_list_translations(sheet, rows, app)
msgs.extend(ms)
else:
# It's a form sheet
ms = update_form_translations(sheet, rows, missing_cols, app)
msgs.extend(ms)
msgs.append(
(messages.success, _("App Translations Updated!"))
)
return msgs
def expected_bulk_app_sheet_headers(app):
'''
Returns lists representing the expected structure of bulk app translation
excel file uploads.
The list will be in the form:
[
["sheetname", ["column name1", "column name 2"]],
["sheet2 name", [...]],
...
]
:param app:
:return:
'''
languages_list = ['default_' + l for l in app.langs]
audio_lang_list = ['audio_' + l for l in app.langs]
image_lang_list = ['image_' + l for l in app.langs]
video_lang_list = ['video_' + l for l in app.langs]
headers = []
# Add headers for the first sheet
headers.append(
["Modules_and_forms",
['Type', 'sheet_name'] + languages_list +
['label_for_cases_%s' % l for l in app.langs] +
['icon_filepath', 'audio_filepath', 'unique_id']]
)
for mod_index, module in enumerate(app.get_modules()):
module_string = "module" + str(mod_index + 1)
headers.append([module_string, ['case_property', 'list_or_detail'] + languages_list])
for form_index, form in enumerate(module.get_forms()):
form_string = module_string + "_form" + str(form_index + 1)
headers.append([
form_string,
["label"] + languages_list + audio_lang_list + image_lang_list
+ video_lang_list
])
return headers
def process_modules_and_forms_sheet(rows, app):
"""
Modify the translations and media references for the modules and forms in
the given app as per the data provided in rows.
This does not save the changes to the database.
:param rows:
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
msgs = []
for row in rows:
identifying_text = row.get('sheet_name', '').split('_')
if len(identifying_text) not in (1, 2):
msgs.append((
messages.error,
'Invalid sheet_name "%s", skipping row.' % row.get(
'sheet_name', ''
)
))
continue
module_index = int(identifying_text[0].replace("module", "")) - 1
try:
document = app.get_module(module_index)
except ModuleNotFoundException:
msgs.append((
messages.error,
'Invalid module in row "%s", skipping row.' % row.get(
'sheet_name'
)
))
continue
if len(identifying_text) == 2:
form_index = int(identifying_text[1].replace("form", "")) - 1
try:
document = document.get_form(form_index)
except FormNotFoundException:
msgs.append((
messages.error,
'Invalid form in row "%s", skipping row.' % row.get(
'sheet_name'
)
))
continue
for lang in app.langs:
translation = row['default_%s' % lang]
if translation:
document.name[lang] = translation
else:
if lang in document.name:
del document.name[lang]
if (has_at_least_one_translation(row, 'label_for_cases', app.langs)
and hasattr(document, 'case_label')):
for lang in app.langs:
translation = row['label_for_cases_%s' % lang]
if translation:
document.case_label[lang] = translation
else:
if lang in document.case_label:
del document.case_label[lang]
image = row.get('icon_filepath', None)
audio = row.get('audio_filepath', None)
if image == '':
image = None
if audio == '':
audio = None
document.media_image = image
document.media_audio = audio
return msgs
def update_form_translations(sheet, rows, missing_cols, app):
"""
Modify the translations of a form given a sheet of translation data.
This does not save the changes to the DB.
:param sheet: a WorksheetJSONReader
:param rows: The rows of the sheet (we can't get this from the sheet
because sheet.__iter__ can only be called once)
:param missing_cols:
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
msgs = []
mod_text, form_text = sheet.worksheet.title.split("_")
module_index = int(mod_text.replace("module", "")) - 1
form_index = int(form_text.replace("form", "")) - 1
form = app.get_module(module_index).get_form(form_index)
if form.source:
xform = form.wrapped_xform()
else:
# This Form doesn't have an xform yet. It is empty.
# Tell the user this?
return msgs
itext = xform.itext_node
assert(itext.exists())
# Make language nodes for each language if they don't yet exist
#
# Currently operating under the assumption that every xForm has at least
# one translation element, that each translation element has a text node
# for each question and that each text node has a value node under it
template_translation_el = None
# Get a translation element to be used as a template for new elements
for lang in app.langs:
trans_el = itext.find("./{f}translation[@lang='%s']" % lang)
if trans_el.exists():
template_translation_el = trans_el
assert(template_translation_el is not None)
# Add missing translation elements
for lang in app.langs:
trans_el = itext.find("./{f}translation[@lang='%s']" % lang)
if not trans_el.exists():
new_trans_el = copy.deepcopy(template_translation_el.xml)
new_trans_el.set('lang', lang)
if lang != app.langs[0]:
# If the language isn't the default language
new_trans_el.attrib.pop('default', None)
else:
new_trans_el.set('default', '')
itext.xml.append(new_trans_el)
# Update the translations
for lang in app.langs:
translation_node = itext.find("./{f}translation[@lang='%s']" % lang)
assert(translation_node.exists())
for row in rows:
label_id = row['label']
text_node = translation_node.find("./{f}text[@id='%s']" % label_id)
if not text_node.exists():
msgs.append((
messages.warning,
"Unrecognized translation label {0} in sheet {1}. That row"
" has been skipped". format(label_id, sheet.worksheet.title)
))
continue
# Add or remove translations
for trans_type in ['default', 'audio', 'image', 'video']:
if trans_type == 'default':
attributes = None
value_node = next(
n for n in text_node.findall("./{f}value")
if 'form' not in n.attrib
)
else:
attributes = {'form': trans_type}
value_node = text_node.find(
"./{f}value[@form='%s']" % trans_type
)
col_key = get_col_key(trans_type, lang)
new_translation = row[col_key]
if not new_translation and col_key not in missing_cols:
# If the cell corresponding to the label for this question
# in this language is empty, fall back to another language
for l in app.langs:
fallback = row[get_col_key(trans_type, l)]
if fallback:
new_translation = fallback
break
if new_translation:
# Create the node if it does not already exist
if not value_node.exists():
e = etree.Element(
"{f}value".format(**namespaces), attributes
)
text_node.xml.append(e)
value_node = WrappedNode(e)
# Update the translation
value_node.xml.text = new_translation
else:
# Remove the node if it already exists
if value_node.exists():
value_node.xml.getparent().remove(value_node.xml)
save_xform(app, form, etree.tostring(xform.xml, encoding="unicode"))
return msgs
def update_case_list_translations(sheet, rows, app):
"""
Modify the translations of a module case list and detail display properties
given a sheet of translation data. The properties in the sheet must be in
the exact same order that they appear in the bulk app translation download.
This function does not save the modified app to the database.
:param sheet:
:param rows: The rows of the sheet (we can't get this from the sheet
because sheet.__iter__ can only be called once)
:param app:
:return: Returns a list of message tuples. The first item in each tuple is
a function like django.contrib.messages.error, and the second is a string.
"""
# The list might contain DetailColumn instances in them that have exactly
# the same attributes (but are in different positions). Therefore we must
# match sheet rows to DetailColumns by position.
msgs = []
module_index = int(sheet.worksheet.title.replace("module", "")) - 1
module = app.get_module(module_index)
# It is easier to process the translations if mapping rows are nested under
# their respective DetailColumns
condensed_rows = []
i = 0
while i < len(rows):
if rows[i]['case_property'].endswith(" (ID Mapping Text)"):
# Cut off the id mapping text
rows[i]['case_property'] = rows[i]['case_property'].split(" ")[0]
# Construct a list of mapping rows
mappings = []
j = 1
while (i + j < len(rows) and
rows[i + j]['case_property'].endswith(" (ID Mapping Value)")):
# Cut off the id mapping value part
rows[i + j]['case_property'] = \
rows[i + j]['case_property'].split(" ")[0]
mappings.append(rows[i + j])
j += 1
rows[i]['mappings'] = mappings
condensed_rows.append(rows[i])
i += j
else:
condensed_rows.append(rows[i])
i += 1
list_rows = [
row for row in condensed_rows if row['list_or_detail'] == 'list'
]
detail_rows = [
row for row in condensed_rows if row['list_or_detail'] == 'detail'
]
short_details = list(module.case_details.short.get_columns())
long_details = list(module.case_details.long.get_columns())
# Check length of lists
for expected_list, received_list, word in [
(short_details, list_rows, "list"),
(long_details, detail_rows, "detail")
]:
if len(expected_list) != len(received_list):
msgs.append((
messages.error,
"Expected {0} case {3} properties in sheet {2}, found {1}. "
"No case list or detail properties for sheet {2} were "
"updated".format(
len(expected_list),
len(received_list),
sheet.worksheet.title,
word
)
))
if msgs:
return msgs
# Update the translations
for row, detail in \
zip(list_rows, short_details) + zip(detail_rows, long_details):
# Check that names match (user is not allowed to change property in the
# upload). Mismatched names indicate the user probably botched the sheet.
if row.get('case_property', None) != detail.field:
msgs.append((
messages.error,
'A row in sheet {sheet} has an unexpected value of "{field}" '
'in the case_property column. Case properties must appear in '
'the same order as they do in the bulk app translation '
'download. No translations updated for this row.'.format(
sheet=sheet.worksheet.title,
field=row.get('case_property', "")
)
))
continue
# The logic for updating a mapping and updating a MappingItem and a
# DetailColumn is almost the same. So, we smush the two together.
for index, translation_row in enumerate([row] + row.get("mappings", [])):
ok_to_delete_translations = has_at_least_one_translation(
translation_row, 'default', app.langs)
if ok_to_delete_translations:
for lang in app.langs:
translation = translation_row['default_%s' % lang]
if index == 0:
# For DetailColumns
language_dict = detail.header
else:
# For MappingItems
language_dict = detail['enum'][index - 1].value
if translation:
language_dict[lang] = translation
else:
if lang in language_dict:
del language_dict[lang]
else:
msgs.append((
messages.error,
"You must provide at least one translation" +
" of the case property '%s'" %
translation_row['case_property'] + " (ID Mapping Value)"
if index != 0 else ""
))
return msgs
def has_at_least_one_translation(row, prefix, langs):
"""
Returns true if the given row has at least one translation.
>>> has_at_least_one_translation(
{'default_en': 'Name', 'case_property': 'name'}, 'default', ['en', 'fra']
)
true
>>> has_at_least_one_translation(
{'case_property': 'name'}, 'default', ['en', 'fra']
)
false
:param row:
:param prefix:
:param langs:
:return:
"""
return bool(filter(None, [row[prefix + '_' + l] for l in langs]))
def get_col_key(translation_type, language):
'''
Returns the name of the column in the bulk app translation spreadsheet
given the translation type and language
:param translation_type: What is being translated, i.e. 'default'
or 'image'
:param language:
:return:
'''
return "%s_%s" % (translation_type, language)
| en | 0.796781 | Process the bulk upload file for the given app. We return these message tuples instead of calling them now to allow this function to be used independently of request objects. :param app: :param f: :return: Returns a list of message tuples. The first item in each tuple is a function like django.contrib.messages.error, and the second is a string. # sheet.__iter__ can only be called once, so cache the result # Convert every key and value to a string # CHECK FOR REPEAT SHEET # CHECK FOR BAD SHEET NAME # CHECK FOR MISSING KEY COLUMN # Several columns on this sheet could be used to uniquely identify # rows. Using sheet_name for now, but unique_id could also be used. # It's a module sheet # It's a form sheet # CHECK FOR MISSING COLUMNS # CHECK FOR EXTRA COLUMNS # NOTE: At the moment there is no missing row detection. # This could be added if we want though # (it is not that bad if a user leaves out a row) # It's the first sheet # It's a module sheet # It's a form sheet Returns lists representing the expected structure of bulk app translation excel file uploads. The list will be in the form: [ ["sheetname", ["column name1", "column name 2"]], ["sheet2 name", [...]], ... ] :param app: :return: # Add headers for the first sheet Modify the translations and media references for the modules and forms in the given app as per the data provided in rows. This does not save the changes to the database. :param rows: :param app: :return: Returns a list of message tuples. The first item in each tuple is a function like django.contrib.messages.error, and the second is a string. Modify the translations of a form given a sheet of translation data. This does not save the changes to the DB. :param sheet: a WorksheetJSONReader :param rows: The rows of the sheet (we can't get this from the sheet because sheet.__iter__ can only be called once) :param missing_cols: :param app: :return: Returns a list of message tuples. The first item in each tuple is a function like django.contrib.messages.error, and the second is a string. # This Form doesn't have an xform yet. It is empty. # Tell the user this? # Make language nodes for each language if they don't yet exist # # Currently operating under the assumption that every xForm has at least # one translation element, that each translation element has a text node # for each question and that each text node has a value node under it # Get a translation element to be used as a template for new elements # Add missing translation elements # If the language isn't the default language # Update the translations # Add or remove translations # If the cell corresponding to the label for this question # in this language is empty, fall back to another language # Create the node if it does not already exist # Update the translation # Remove the node if it already exists Modify the translations of a module case list and detail display properties given a sheet of translation data. The properties in the sheet must be in the exact same order that they appear in the bulk app translation download. This function does not save the modified app to the database. :param sheet: :param rows: The rows of the sheet (we can't get this from the sheet because sheet.__iter__ can only be called once) :param app: :return: Returns a list of message tuples. The first item in each tuple is a function like django.contrib.messages.error, and the second is a string. # The list might contain DetailColumn instances in them that have exactly # the same attributes (but are in different positions). Therefore we must # match sheet rows to DetailColumns by position. # It is easier to process the translations if mapping rows are nested under # their respective DetailColumns # Cut off the id mapping text # Construct a list of mapping rows # Cut off the id mapping value part # Check length of lists # Update the translations # Check that names match (user is not allowed to change property in the # upload). Mismatched names indicate the user probably botched the sheet. # The logic for updating a mapping and updating a MappingItem and a # DetailColumn is almost the same. So, we smush the two together. # For DetailColumns # For MappingItems Returns true if the given row has at least one translation. >>> has_at_least_one_translation( {'default_en': 'Name', 'case_property': 'name'}, 'default', ['en', 'fra'] ) true >>> has_at_least_one_translation( {'case_property': 'name'}, 'default', ['en', 'fra'] ) false :param row: :param prefix: :param langs: :return: Returns the name of the column in the bulk app translation spreadsheet given the translation type and language :param translation_type: What is being translated, i.e. 'default' or 'image' :param language: :return: | 2.115909 | 2 |
scripts/hf_create_train_test.py | myutman/contracode | 115 | 6620559 | <reponame>myutman/contracode<filename>scripts/hf_create_train_test.py
from pathlib import Path
import numpy as np
import pandas as pd
import pickle
import gzip
from tqdm.auto import tqdm
DATA_PICKLE_PATH = Path("data/codesearchnet_javascript/javascript_augmented.pickle.gz")
CACHE_PATH = Path("data/hf_data/augmented_pretrain_data_df.parquet")
TRAIN_OUT_PATH = Path("/data/paras/augmented_pretrain_df.train.pickle.gz")
TEST_OUT_PATH = Path("/data/paras/augmented_pretrain_df.test.pickle.gz")
TRAIN_OUT_TXT_PATH = Path("/data/paras/augmented_pretrain_df.train.txt")
TEST_OUT_TXT_PATH = Path("/data/paras/augmented_pretrain_df.test.txt")
if __name__ == "__main__":
if CACHE_PATH.exists():
print("Loading from cache")
df = pd.read_parquet(CACHE_PATH)
else:
print("Loading from pickle")
with gzip.open(DATA_PICKLE_PATH) as f:
data = pickle.load(f)
flattened_data = []
for idx, x in enumerate(tqdm(data)):
for item in x:
flattened_data.append(dict(data_idx=idx, text=item))
df = pd.DataFrame(flattened_data)
del data, flattened_data
print("Saving cache file of dataframe")
df.to_parquet(str(CACHE_PATH.resolve()), engine="pyarrow")
data_idxs = np.asarray(list(set(df["data_idx"])))
np.random.shuffle(data_idxs)
test_idxs, train_idxs = data_idxs[:10000], data_idxs[10000:]
train_df = df[df["data_idx"].isin(train_idxs)].sample(frac=1).reset_index(drop=True)
test_df = df[df["data_idx"].isin(test_idxs)].sample(frac=1).reset_index(drop=True)
print("Saving train data")
train_df.to_pickle(TRAIN_OUT_PATH)
print("Saving test data")
test_df.to_pickle(TEST_OUT_PATH)
train_txt = train_df["text"].tolist()
test_txt = test_df["text"].tolist()
print("Saving train text")
with TRAIN_OUT_TXT_PATH.open("w") as f:
f.write("\n".join(train_txt))
print("Saving test text")
with TEST_OUT_TXT_PATH.open("w") as f:
f.write("\n".join(test_txt))
| from pathlib import Path
import numpy as np
import pandas as pd
import pickle
import gzip
from tqdm.auto import tqdm
DATA_PICKLE_PATH = Path("data/codesearchnet_javascript/javascript_augmented.pickle.gz")
CACHE_PATH = Path("data/hf_data/augmented_pretrain_data_df.parquet")
TRAIN_OUT_PATH = Path("/data/paras/augmented_pretrain_df.train.pickle.gz")
TEST_OUT_PATH = Path("/data/paras/augmented_pretrain_df.test.pickle.gz")
TRAIN_OUT_TXT_PATH = Path("/data/paras/augmented_pretrain_df.train.txt")
TEST_OUT_TXT_PATH = Path("/data/paras/augmented_pretrain_df.test.txt")
if __name__ == "__main__":
if CACHE_PATH.exists():
print("Loading from cache")
df = pd.read_parquet(CACHE_PATH)
else:
print("Loading from pickle")
with gzip.open(DATA_PICKLE_PATH) as f:
data = pickle.load(f)
flattened_data = []
for idx, x in enumerate(tqdm(data)):
for item in x:
flattened_data.append(dict(data_idx=idx, text=item))
df = pd.DataFrame(flattened_data)
del data, flattened_data
print("Saving cache file of dataframe")
df.to_parquet(str(CACHE_PATH.resolve()), engine="pyarrow")
data_idxs = np.asarray(list(set(df["data_idx"])))
np.random.shuffle(data_idxs)
test_idxs, train_idxs = data_idxs[:10000], data_idxs[10000:]
train_df = df[df["data_idx"].isin(train_idxs)].sample(frac=1).reset_index(drop=True)
test_df = df[df["data_idx"].isin(test_idxs)].sample(frac=1).reset_index(drop=True)
print("Saving train data")
train_df.to_pickle(TRAIN_OUT_PATH)
print("Saving test data")
test_df.to_pickle(TEST_OUT_PATH)
train_txt = train_df["text"].tolist()
test_txt = test_df["text"].tolist()
print("Saving train text")
with TRAIN_OUT_TXT_PATH.open("w") as f:
f.write("\n".join(train_txt))
print("Saving test text")
with TEST_OUT_TXT_PATH.open("w") as f:
f.write("\n".join(test_txt)) | none | 1 | 2.454115 | 2 | |
Python/task1-3/c2/blur.py | QH17/QHimage | 4 | 6620560 | <filename>Python/task1-3/c2/blur.py<gh_stars>1-10
#均值滤波函数
import cv2
img = cv2.imread("2.jpg")
#########################################################################
#cv2.blur(
# InputArray src, 输入的图像
# OutputArray dst, 输出的图像
# Size Ksize, 卷积核大小
# Point Anchor = (-1,-1), 锚点坐标
# int borderType=BORDER_DEFAULT 边界类型
# )
#
#将核的锚点放在该特定位置的像素上，同时，核内的其他值与该像素邻域的各像素重合；
#将核内各值与相应像素值相乘，并将乘积相加；
#将所得结果放到与锚点对应的像素上；
#对图像所有像素重复上述过程。
#
#########################################################################
dst = cv2.blur(img,(5,5))
cv2.imshow("before", img)
cv2.imshow("after", dst)
cv2.waitKey(0)
| <filename>Python/task1-3/c2/blur.py<gh_stars>1-10
#均值滤波函数
import cv2
img = cv2.imread("2.jpg")
#########################################################################
#cv2.blur(
# InputArray src, 输入的图像
# OutputArray dst, 输出的图像
# Size Ksize, 卷积核大小
# Point Anchor = (-1,-1), 锚点坐标
# int borderType=BORDER_DEFAULT 边界类型
# )
#
#将核的锚点放在该特定位置的像素上，同时，核内的其他值与该像素邻域的各像素重合；
#将核内各值与相应像素值相乘，并将乘积相加；
#将所得结果放到与锚点对应的像素上；
#对图像所有像素重复上述过程。
#
#########################################################################
dst = cv2.blur(img,(5,5))
cv2.imshow("before", img)
cv2.imshow("after", dst)
cv2.waitKey(0)
| zh | 0.653718 | #均值滤波函数 ######################################################################### #cv2.blur( # InputArray src, 输入的图像 # OutputArray dst, 输出的图像 # Size Ksize, 卷积核大小 # Point Anchor = (-1,-1), 锚点坐标 # int borderType=BORDER_DEFAULT 边界类型 # ) # #将核的锚点放在该特定位置的像素上，同时，核内的其他值与该像素邻域的各像素重合； #将核内各值与相应像素值相乘，并将乘积相加； #将所得结果放到与锚点对应的像素上； #对图像所有像素重复上述过程。 # ######################################################################### | 3.576786 | 4 |
src/merry/__init__.py | miguelgrinberg/merry | 140 | 6620561 | <filename>src/merry/__init__.py
from functools import wraps
import inspect
import logging
getargspec = None
if getattr(inspect, 'getfullargspec', None):
getargspec = inspect.getfullargspec
else:
# this one is deprecated in Python 3, but available in Python 2
getargspec = inspect.getargspec
class _Namespace:
pass
class Merry(object):
"""Initialze merry.
:param logger_name: the logger name to use. The default is ``'merry'``.
:param debug: set to ``True`` to enable debug mode, which causes all
errors to bubble up so that a debugger can catch them. The
default is ``False``.
"""
def __init__(self, logger_name='merry', debug=False):
self.logger = logging.getLogger(logger_name)
self.g = _Namespace()
self.debug = debug
self.except_ = {}
self.force_debug = []
self.force_handle = []
self.else_ = None
self.finally_ = None
def _try(self, f):
"""Decorator that wraps a function in a try block.
Example usage::
@merry._try
def my_function():
# do something here
"""
@wraps(f)
def wrapper(*args, **kwargs):
ret = None
try:
ret = f(*args, **kwargs)
# note that if the function returned something, the else clause
# will be skipped. This is a similar behavior to a normal
# try/except/else block.
if ret is not None:
return ret
except Exception as e:
# find the best handler for this exception
handler = None
for c in self.except_.keys():
if isinstance(e, c):
if handler is None or issubclass(c, handler):
handler = c
# if we don't have any handler, we let the exception bubble up
if handler is None:
raise e
# log exception
self.logger.exception('[merry] Exception caught')
# if in debug mode, then bubble up to let a debugger handle
debug = self.debug
if handler in self.force_debug:
debug = True
elif handler in self.force_handle:
debug = False
if debug:
raise e
# invoke handler
if len(getargspec(self.except_[handler])[0]) == 0:
return self.except_[handler]()
else:
return self.except_[handler](e)
else:
# if we have an else handler, call it now
if self.else_ is not None:
return self.else_()
finally:
# if we have a finally handler, call it now
if self.finally_ is not None:
alt_ret = self.finally_()
if alt_ret is not None:
ret = alt_ret
return ret
return wrapper
def _except(self, *args, **kwargs):
"""Decorator that registers a function as an error handler for one or
more exception classes.
Example usage::
@merry._except(RuntimeError)
def runtime_error_handler(e):
print('runtime error:', str(e))
:param args: the list of exception classes to be handled by the
decorated function.
:param kwargs: configuration arguments. Pass ``debug=True`` to enable
debug mode for this handler, which bubbles up all
exceptions. Pass ``debug=False`` to prevent the error
from bubbling up, even if debug mode is enabled
globally.
"""
def decorator(f):
for e in args:
self.except_[e] = f
d = kwargs.get('debug', None)
if d:
self.force_debug.append(e)
elif d is not None:
self.force_handle.append(e)
return f
return decorator
def _else(self, f):
"""Decorator to define the ``else`` clause handler.
Example usage::
@merry._else
def else_handler():
print('no exceptions were raised')
"""
self.else_ = f
return f
def _finally(self, f):
"""Decorator to define the ``finally`` clause handler.
Example usage::
@merry._finally
def finally_handler():
print('clean up')
"""
self.finally_ = f
return f
| <filename>src/merry/__init__.py
from functools import wraps
import inspect
import logging
getargspec = None
if getattr(inspect, 'getfullargspec', None):
getargspec = inspect.getfullargspec
else:
# this one is deprecated in Python 3, but available in Python 2
getargspec = inspect.getargspec
class _Namespace:
pass
class Merry(object):
"""Initialze merry.
:param logger_name: the logger name to use. The default is ``'merry'``.
:param debug: set to ``True`` to enable debug mode, which causes all
errors to bubble up so that a debugger can catch them. The
default is ``False``.
"""
def __init__(self, logger_name='merry', debug=False):
self.logger = logging.getLogger(logger_name)
self.g = _Namespace()
self.debug = debug
self.except_ = {}
self.force_debug = []
self.force_handle = []
self.else_ = None
self.finally_ = None
def _try(self, f):
"""Decorator that wraps a function in a try block.
Example usage::
@merry._try
def my_function():
# do something here
"""
@wraps(f)
def wrapper(*args, **kwargs):
ret = None
try:
ret = f(*args, **kwargs)
# note that if the function returned something, the else clause
# will be skipped. This is a similar behavior to a normal
# try/except/else block.
if ret is not None:
return ret
except Exception as e:
# find the best handler for this exception
handler = None
for c in self.except_.keys():
if isinstance(e, c):
if handler is None or issubclass(c, handler):
handler = c
# if we don't have any handler, we let the exception bubble up
if handler is None:
raise e
# log exception
self.logger.exception('[merry] Exception caught')
# if in debug mode, then bubble up to let a debugger handle
debug = self.debug
if handler in self.force_debug:
debug = True
elif handler in self.force_handle:
debug = False
if debug:
raise e
# invoke handler
if len(getargspec(self.except_[handler])[0]) == 0:
return self.except_[handler]()
else:
return self.except_[handler](e)
else:
# if we have an else handler, call it now
if self.else_ is not None:
return self.else_()
finally:
# if we have a finally handler, call it now
if self.finally_ is not None:
alt_ret = self.finally_()
if alt_ret is not None:
ret = alt_ret
return ret
return wrapper
def _except(self, *args, **kwargs):
"""Decorator that registers a function as an error handler for one or
more exception classes.
Example usage::
@merry._except(RuntimeError)
def runtime_error_handler(e):
print('runtime error:', str(e))
:param args: the list of exception classes to be handled by the
decorated function.
:param kwargs: configuration arguments. Pass ``debug=True`` to enable
debug mode for this handler, which bubbles up all
exceptions. Pass ``debug=False`` to prevent the error
from bubbling up, even if debug mode is enabled
globally.
"""
def decorator(f):
for e in args:
self.except_[e] = f
d = kwargs.get('debug', None)
if d:
self.force_debug.append(e)
elif d is not None:
self.force_handle.append(e)
return f
return decorator
def _else(self, f):
"""Decorator to define the ``else`` clause handler.
Example usage::
@merry._else
def else_handler():
print('no exceptions were raised')
"""
self.else_ = f
return f
def _finally(self, f):
"""Decorator to define the ``finally`` clause handler.
Example usage::
@merry._finally
def finally_handler():
print('clean up')
"""
self.finally_ = f
return f
| en | 0.769538 | # this one is deprecated in Python 3, but available in Python 2 Initialze merry. :param logger_name: the logger name to use. The default is ``'merry'``. :param debug: set to ``True`` to enable debug mode, which causes all errors to bubble up so that a debugger can catch them. The default is ``False``. Decorator that wraps a function in a try block. Example usage:: @merry._try def my_function(): # do something here # note that if the function returned something, the else clause # will be skipped. This is a similar behavior to a normal # try/except/else block. # find the best handler for this exception # if we don't have any handler, we let the exception bubble up # log exception # if in debug mode, then bubble up to let a debugger handle # invoke handler # if we have an else handler, call it now # if we have a finally handler, call it now Decorator that registers a function as an error handler for one or more exception classes. Example usage:: @merry._except(RuntimeError) def runtime_error_handler(e): print('runtime error:', str(e)) :param args: the list of exception classes to be handled by the decorated function. :param kwargs: configuration arguments. Pass ``debug=True`` to enable debug mode for this handler, which bubbles up all exceptions. Pass ``debug=False`` to prevent the error from bubbling up, even if debug mode is enabled globally. Decorator to define the ``else`` clause handler. Example usage:: @merry._else def else_handler(): print('no exceptions were raised') Decorator to define the ``finally`` clause handler. Example usage:: @merry._finally def finally_handler(): print('clean up') | 2.804784 | 3 |
create_django_project/utils.py | ZendaInnocent/create-django-project | 0 | 6620562 | from pathlib import Path
import re
def read_secret_key(settings_file: Path):
settings = settings_file.read_text()
pattern = re.compile(r"secret_key", re.IGNORECASE)
results = [line for line in settings.rsplit('\n') if pattern.findall(line)]
secret_key = results[0].split(' = ')[1]
return secret_key
| from pathlib import Path
import re
def read_secret_key(settings_file: Path):
settings = settings_file.read_text()
pattern = re.compile(r"secret_key", re.IGNORECASE)
results = [line for line in settings.rsplit('\n') if pattern.findall(line)]
secret_key = results[0].split(' = ')[1]
return secret_key
| none | 1 | 2.929866 | 3 | |
babysage/__init__.py | ayemos/babysage | 5 | 6620563 | <gh_stars>1-10
# -*- coding: utf-8 -*-
"""Top-level package for Babysage."""
__author__ = """ayemos"""
__email__ = '<EMAIL>'
__version__ = '0.1.0'
| # -*- coding: utf-8 -*-
"""Top-level package for Babysage."""
__author__ = """ayemos"""
__email__ = '<EMAIL>'
__version__ = '0.1.0' | en | 0.63091 | # -*- coding: utf-8 -*- Top-level package for Babysage. ayemos | 0.866212 | 1 |
sme_material_apps/proponentes/migrations/0015_auto_20200813_1611.py | luizhpriotto/piloto_apresentacao | 0 | 6620564 | <reponame>luizhpriotto/piloto_apresentacao
# Generated by Django 2.2.9 on 2020-08-13 19:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('proponentes', '0014_auto_20200812_1620'),
]
operations = [
migrations.AddField(
model_name='anexo',
name='data_validade',
field=models.DateField(blank=True, null=True),
),
migrations.AddField(
model_name='tipodocumento',
name='tem_data_validade',
field=models.BooleanField(default=False),
),
]
| # Generated by Django 2.2.9 on 2020-08-13 19:11
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('proponentes', '0014_auto_20200812_1620'),
]
operations = [
migrations.AddField(
model_name='anexo',
name='data_validade',
field=models.DateField(blank=True, null=True),
),
migrations.AddField(
model_name='tipodocumento',
name='tem_data_validade',
field=models.BooleanField(default=False),
),
] | en | 0.801212 | # Generated by Django 2.2.9 on 2020-08-13 19:11 | 1.497339 | 1 |
python/hackerrank/combinations/main.py | imjoseangel/sandbox | 0 | 6620565 | <filename>python/hackerrank/combinations/main.py<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (division, absolute_import, print_function,
unicode_literals)
from itertools import combinations
def main():
n, m = input().split()
for item in range(1, int(m) + 1):
print(*[''.join(i)
for i in combinations(sorted(n), int(item))], sep='\n')
if __name__ == '__main__':
main()
| <filename>python/hackerrank/combinations/main.py<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (division, absolute_import, print_function,
unicode_literals)
from itertools import combinations
def main():
n, m = input().split()
for item in range(1, int(m) + 1):
print(*[''.join(i)
for i in combinations(sorted(n), int(item))], sep='\n')
if __name__ == '__main__':
main()
| en | 0.352855 | #!/usr/bin/env python # -*- coding: utf-8 -*- | 3.330702 | 3 |
jpype/_jio.py | rbprogrammer/jpype | 0 | 6620566 | #*****************************************************************************
# Copyright 2017 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#*****************************************************************************
from . import _jclass
from . import JavaException
import sys as _sys
if _sys.version > '3':
pass
def _closeableExit(self,exception_type, exception_value, traceback):
info = _sys.exc_info()
try:
self.close()
except JavaException as jex:
# Eat the second exception if we are already handling one.
if (info[0]==None):
raise jex
pass
def _closeableEnter(self):
return self
class CloseableCustomizer(object):
_METHODS = {
'__enter__': _closeableEnter,
'__exit__': _closeableExit,
}
def canCustomize(self, name, jc):
if name == 'java.io.Closeable':
return True
return False
def customize(self, name, jc, bases, members):
members.update(CloseableCustomizer._METHODS)
_jclass.registerClassCustomizer(CloseableCustomizer())
| #*****************************************************************************
# Copyright 2017 <NAME>
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#*****************************************************************************
from . import _jclass
from . import JavaException
import sys as _sys
if _sys.version > '3':
pass
def _closeableExit(self,exception_type, exception_value, traceback):
info = _sys.exc_info()
try:
self.close()
except JavaException as jex:
# Eat the second exception if we are already handling one.
if (info[0]==None):
raise jex
pass
def _closeableEnter(self):
return self
class CloseableCustomizer(object):
_METHODS = {
'__enter__': _closeableEnter,
'__exit__': _closeableExit,
}
def canCustomize(self, name, jc):
if name == 'java.io.Closeable':
return True
return False
def customize(self, name, jc, bases, members):
members.update(CloseableCustomizer._METHODS)
_jclass.registerClassCustomizer(CloseableCustomizer())
| en | 0.750441 | #***************************************************************************** # Copyright 2017 <NAME> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # #***************************************************************************** # Eat the second exception if we are already handling one. | 2.131315 | 2 |
asyncfileserver/tests/unit/model/test_confirm_put_queue.py | tarc/echo_server | 1 | 6620567 | <filename>asyncfileserver/tests/unit/model/test_confirm_put_queue.py
import asyncio
import aiounittest
from asyncfileserver.model.confirm_put_queue import ConfirmPutQueue
from asyncfileserver.tests.unit.model.fake_async_queue import FakeAsyncQueue
class AllowAll(object):
async def should_put(self, item):
# Release control back to event loop to simulate more properly an async
# call.
await asyncio.sleep(0)
return True
class AllowSome(object):
def __init__(self, items):
self._items = items
self._index = 0
async def should_put(self, item):
await asyncio.sleep(0)
if self._index >= len(self._items):
return False
if item == self._items[self._index]:
self._index = self._index + 1
return True
return False
class TestConfirmPutQueue(aiounittest.AsyncTestCase):
@staticmethod
async def _compose_get_task_done(queue):
item = await queue.get()
queue.task_done()
return item
def get_event_loop(self):
return asyncio.get_event_loop()
async def test_allow_all_arbiter(self):
allow_all = AllowAll()
queue = []
fake_queue = FakeAsyncQueue(queue)
confirm_queue = ConfirmPutQueue(allow_all, fake_queue)
singular_item = bytearray(b'')
put_task = asyncio.create_task(confirm_queue.put(singular_item))
get_task = asyncio.create_task(
self._compose_get_task_done(confirm_queue))
_, same_element = await asyncio.gather(put_task, get_task)
self.assertEqual(same_element, b'')
async def test_allow_some_elements(self):
allowed_bytes = [bytes([i]) for i in (1, 3, 5, 7, 9)]
allowed_bytearrays = [bytearray(i) for i in allowed_bytes]
allow_some = AllowSome(allowed_bytearrays)
queue = []
fake_queue = FakeAsyncQueue(queue)
confirm_queue = ConfirmPutQueue(allow_some, fake_queue)
put_tasks = [asyncio.create_task(
confirm_queue.put(bytearray([i]))) for i in range(10)]
get_tasks = [asyncio.create_task(
self._compose_get_task_done(confirm_queue)) for _ in range(5)]
* results, = await asyncio.gather(* get_tasks, * put_tasks)
self.assertEqual(results[0:5], allowed_bytes)
| <filename>asyncfileserver/tests/unit/model/test_confirm_put_queue.py
import asyncio
import aiounittest
from asyncfileserver.model.confirm_put_queue import ConfirmPutQueue
from asyncfileserver.tests.unit.model.fake_async_queue import FakeAsyncQueue
class AllowAll(object):
async def should_put(self, item):
# Release control back to event loop to simulate more properly an async
# call.
await asyncio.sleep(0)
return True
class AllowSome(object):
def __init__(self, items):
self._items = items
self._index = 0
async def should_put(self, item):
await asyncio.sleep(0)
if self._index >= len(self._items):
return False
if item == self._items[self._index]:
self._index = self._index + 1
return True
return False
class TestConfirmPutQueue(aiounittest.AsyncTestCase):
@staticmethod
async def _compose_get_task_done(queue):
item = await queue.get()
queue.task_done()
return item
def get_event_loop(self):
return asyncio.get_event_loop()
async def test_allow_all_arbiter(self):
allow_all = AllowAll()
queue = []
fake_queue = FakeAsyncQueue(queue)
confirm_queue = ConfirmPutQueue(allow_all, fake_queue)
singular_item = bytearray(b'')
put_task = asyncio.create_task(confirm_queue.put(singular_item))
get_task = asyncio.create_task(
self._compose_get_task_done(confirm_queue))
_, same_element = await asyncio.gather(put_task, get_task)
self.assertEqual(same_element, b'')
async def test_allow_some_elements(self):
allowed_bytes = [bytes([i]) for i in (1, 3, 5, 7, 9)]
allowed_bytearrays = [bytearray(i) for i in allowed_bytes]
allow_some = AllowSome(allowed_bytearrays)
queue = []
fake_queue = FakeAsyncQueue(queue)
confirm_queue = ConfirmPutQueue(allow_some, fake_queue)
put_tasks = [asyncio.create_task(
confirm_queue.put(bytearray([i]))) for i in range(10)]
get_tasks = [asyncio.create_task(
self._compose_get_task_done(confirm_queue)) for _ in range(5)]
* results, = await asyncio.gather(* get_tasks, * put_tasks)
self.assertEqual(results[0:5], allowed_bytes)
| en | 0.843479 | # Release control back to event loop to simulate more properly an async # call. | 2.456002 | 2 |
uncertaintorch/models/resnet3d.py | jcreinhold/uncertaintorch | 1 | 6620568 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
resnet3d
3d resnet model (backbone for deeplabv3)
Author: <NAME> (<EMAIL>)
Created on: December 31, 2019
"""
__all__ = ['ResNet3d', 'resnet3d18', 'resnet3d34', 'resnet3d50', 'resnet3d101']
import torch
from torch import nn
import torch.nn.functional as F
BASE_WIDTH = 32
EXPANSION = 2
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Sequential(nn.ReplicationPad3d(dilation),
nn.Conv3d(in_planes, out_planes, kernel_size=3, stride=stride,
groups=groups, bias=False, dilation=dilation))
def conv1x1(in_planes, out_planes, stride=1):
"""1x1 convolution"""
return nn.Conv3d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False)
class Bottleneck(nn.Module):
expansion = EXPANSION
__constants__ = ['downsample']
def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
base_width=BASE_WIDTH, dilation=1, norm_layer=None):
super(Bottleneck, self).__init__()
if norm_layer is None:
norm_layer = nn.BatchNorm3d
width = int(planes * (base_width / BASE_WIDTH)) * groups
# Both self.conv2 and self.downsample layers downsample the input when stride != 1
self.conv1 = conv1x1(inplanes, width)
self.bn1 = norm_layer(width)
self.conv2 = conv3x3(width, width, stride, groups, dilation)
self.bn2 = norm_layer(width)
self.conv3 = conv1x1(width, planes * self.expansion)
self.bn3 = norm_layer(planes * self.expansion)
self.relu = nn.ReLU(inplace=True)
self.downsample = downsample
self.stride = stride
def forward(self, x):
identity = x
out = self.conv1(x)
out = self.bn1(out)
out = self.relu(out)
out = self.conv2(out)
out = self.bn2(out)
out = self.relu(out)
out = self.conv3(out)
out = self.bn3(out)
if self.downsample is not None:
identity = self.downsample(x)
out += identity
out = self.relu(out)
return out
class ResNet3d(nn.Module):
def __init__(self, block, layers, zero_init_residual=False,
groups=1, width_per_group=BASE_WIDTH, replace_stride_with_dilation=None,
norm_layer=None, in_channels=1, dropout_rate=0., bayesian=False):
super(ResNet3d, self).__init__()
if norm_layer is None:
norm_layer = nn.BatchNorm3d
self._norm_layer = norm_layer
self.p = dropout_rate
self.bayesian = bayesian
self.inplanes = BASE_WIDTH
self.dilation = 1
if replace_stride_with_dilation is None:
# each element in the tuple indicates if we should replace
# the 2x2 stride with a dilated convolution instead
replace_stride_with_dilation = [False, False, False]
if len(replace_stride_with_dilation) != 3:
raise ValueError("replace_stride_with_dilation should be None "
"or a 3-element tuple, got {}".format(replace_stride_with_dilation))
self.groups = groups
self.base_width = width_per_group
self.conv1 = nn.Sequential(nn.ReplicationPad3d(3),
nn.Conv3d(in_channels, self.inplanes, kernel_size=7, stride=2, bias=False))
self.bn1 = norm_layer(self.inplanes)
self.relu = nn.ReLU(inplace=True)
self.maxpool = nn.MaxPool3d(kernel_size=3, stride=2, padding=1)
self.layer1 = self._make_layer(block, BASE_WIDTH, layers[0])
self.layer2 = self._make_layer(block, BASE_WIDTH*2, layers[1], stride=2,
dilate=replace_stride_with_dilation[0])
self.layer3 = self._make_layer(block, BASE_WIDTH*(2 if replace_stride_with_dilation[0] else 4),
layers[2], stride=2, dilate=replace_stride_with_dilation[1])
self.layer4 = self._make_layer(block, BASE_WIDTH*(2 if replace_stride_with_dilation[1] else 8),
layers[3], stride=2, dilate=replace_stride_with_dilation[2])
for m in self.modules():
if isinstance(m, nn.Conv3d):
nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
elif isinstance(m, (nn.BatchNorm3d, nn.GroupNorm)):
nn.init.constant_(m.weight, 1)
nn.init.constant_(m.bias, 0)
# Zero-initialize the last BN in each residual branch,
# so that the residual branch starts with zeros, and each residual block behaves like an identity.
# This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677
if zero_init_residual:
for m in self.modules():
if isinstance(m, Bottleneck):
nn.init.constant_(m.bn3.weight, 0)
def dropout(self, x):
use_dropout = self.training or self.bayesian
return F.dropout3d(x, self.p, training=use_dropout, inplace=False)
def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
norm_layer = self._norm_layer
downsample = None
previous_dilation = self.dilation
if dilate:
self.dilation *= stride
stride = 1
if stride != 1 or self.inplanes != planes * block.expansion:
downsample = nn.Sequential(
conv1x1(self.inplanes, planes * block.expansion, stride),
norm_layer(planes * block.expansion),
)
layers = []
layers.append(block(self.inplanes, planes, stride, downsample, self.groups,
self.base_width, previous_dilation, norm_layer))
self.inplanes = planes * block.expansion
for _ in range(1, blocks):
layers.append(block(self.inplanes, planes, groups=self.groups,
base_width=self.base_width, dilation=self.dilation,
norm_layer=norm_layer))
return nn.Sequential(*layers)
def _forward_impl(self, x):
# See note [TorchScript super()]
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
start = x.clone()
x = self.maxpool(x)
x = self.layer1(x)
mid = x.clone()
x = self.dropout(x)
x = self.dropout(self.layer2(x))
x = self.dropout(self.layer3(x))
x = self.dropout(self.layer4(x))
return x, start, mid
def forward(self, x):
return self._forward_impl(x)
def resnet3d18(**kwargs):
return ResNet3d(Bottleneck, [2, 2, 2, 2], **kwargs)
def resnet3d34(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 6, 3], **kwargs)
def resnet3d50(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 6, 3], **kwargs)
def resnet3d101(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 23, 3], **kwargs)
| #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
resnet3d
3d resnet model (backbone for deeplabv3)
Author: <NAME> (<EMAIL>)
Created on: December 31, 2019
"""
__all__ = ['ResNet3d', 'resnet3d18', 'resnet3d34', 'resnet3d50', 'resnet3d101']
import torch
from torch import nn
import torch.nn.functional as F
BASE_WIDTH = 32
EXPANSION = 2
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
"""3x3 convolution with padding"""
return nn.Sequential(nn.ReplicationPad3d(dilation),
nn.Conv3d(in_planes, out_planes, kernel_size=3, stride=stride,
groups=groups, bias=False, dilation=dilation))
def conv1x1(in_planes, out_planes, stride=1):
"""1x1 convolution"""
return nn.Conv3d(in_planes, out_planes, kernel_size=1, stride=stride, bias=False)
class Bottleneck(nn.Module):
expansion = EXPANSION
__constants__ = ['downsample']
def __init__(self, inplanes, planes, stride=1, downsample=None, groups=1,
base_width=BASE_WIDTH, dilation=1, norm_layer=None):
super(Bottleneck, self).__init__()
if norm_layer is None:
norm_layer = nn.BatchNorm3d
width = int(planes * (base_width / BASE_WIDTH)) * groups
# Both self.conv2 and self.downsample layers downsample the input when stride != 1
self.conv1 = conv1x1(inplanes, width)
self.bn1 = norm_layer(width)
self.conv2 = conv3x3(width, width, stride, groups, dilation)
self.bn2 = norm_layer(width)
self.conv3 = conv1x1(width, planes * self.expansion)
self.bn3 = norm_layer(planes * self.expansion)
self.relu = nn.ReLU(inplace=True)
self.downsample = downsample
self.stride = stride
def forward(self, x):
identity = x
out = self.conv1(x)
out = self.bn1(out)
out = self.relu(out)
out = self.conv2(out)
out = self.bn2(out)
out = self.relu(out)
out = self.conv3(out)
out = self.bn3(out)
if self.downsample is not None:
identity = self.downsample(x)
out += identity
out = self.relu(out)
return out
class ResNet3d(nn.Module):
def __init__(self, block, layers, zero_init_residual=False,
groups=1, width_per_group=BASE_WIDTH, replace_stride_with_dilation=None,
norm_layer=None, in_channels=1, dropout_rate=0., bayesian=False):
super(ResNet3d, self).__init__()
if norm_layer is None:
norm_layer = nn.BatchNorm3d
self._norm_layer = norm_layer
self.p = dropout_rate
self.bayesian = bayesian
self.inplanes = BASE_WIDTH
self.dilation = 1
if replace_stride_with_dilation is None:
# each element in the tuple indicates if we should replace
# the 2x2 stride with a dilated convolution instead
replace_stride_with_dilation = [False, False, False]
if len(replace_stride_with_dilation) != 3:
raise ValueError("replace_stride_with_dilation should be None "
"or a 3-element tuple, got {}".format(replace_stride_with_dilation))
self.groups = groups
self.base_width = width_per_group
self.conv1 = nn.Sequential(nn.ReplicationPad3d(3),
nn.Conv3d(in_channels, self.inplanes, kernel_size=7, stride=2, bias=False))
self.bn1 = norm_layer(self.inplanes)
self.relu = nn.ReLU(inplace=True)
self.maxpool = nn.MaxPool3d(kernel_size=3, stride=2, padding=1)
self.layer1 = self._make_layer(block, BASE_WIDTH, layers[0])
self.layer2 = self._make_layer(block, BASE_WIDTH*2, layers[1], stride=2,
dilate=replace_stride_with_dilation[0])
self.layer3 = self._make_layer(block, BASE_WIDTH*(2 if replace_stride_with_dilation[0] else 4),
layers[2], stride=2, dilate=replace_stride_with_dilation[1])
self.layer4 = self._make_layer(block, BASE_WIDTH*(2 if replace_stride_with_dilation[1] else 8),
layers[3], stride=2, dilate=replace_stride_with_dilation[2])
for m in self.modules():
if isinstance(m, nn.Conv3d):
nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
elif isinstance(m, (nn.BatchNorm3d, nn.GroupNorm)):
nn.init.constant_(m.weight, 1)
nn.init.constant_(m.bias, 0)
# Zero-initialize the last BN in each residual branch,
# so that the residual branch starts with zeros, and each residual block behaves like an identity.
# This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677
if zero_init_residual:
for m in self.modules():
if isinstance(m, Bottleneck):
nn.init.constant_(m.bn3.weight, 0)
def dropout(self, x):
use_dropout = self.training or self.bayesian
return F.dropout3d(x, self.p, training=use_dropout, inplace=False)
def _make_layer(self, block, planes, blocks, stride=1, dilate=False):
norm_layer = self._norm_layer
downsample = None
previous_dilation = self.dilation
if dilate:
self.dilation *= stride
stride = 1
if stride != 1 or self.inplanes != planes * block.expansion:
downsample = nn.Sequential(
conv1x1(self.inplanes, planes * block.expansion, stride),
norm_layer(planes * block.expansion),
)
layers = []
layers.append(block(self.inplanes, planes, stride, downsample, self.groups,
self.base_width, previous_dilation, norm_layer))
self.inplanes = planes * block.expansion
for _ in range(1, blocks):
layers.append(block(self.inplanes, planes, groups=self.groups,
base_width=self.base_width, dilation=self.dilation,
norm_layer=norm_layer))
return nn.Sequential(*layers)
def _forward_impl(self, x):
# See note [TorchScript super()]
x = self.conv1(x)
x = self.bn1(x)
x = self.relu(x)
start = x.clone()
x = self.maxpool(x)
x = self.layer1(x)
mid = x.clone()
x = self.dropout(x)
x = self.dropout(self.layer2(x))
x = self.dropout(self.layer3(x))
x = self.dropout(self.layer4(x))
return x, start, mid
def forward(self, x):
return self._forward_impl(x)
def resnet3d18(**kwargs):
return ResNet3d(Bottleneck, [2, 2, 2, 2], **kwargs)
def resnet3d34(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 6, 3], **kwargs)
def resnet3d50(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 6, 3], **kwargs)
def resnet3d101(**kwargs):
return ResNet3d(Bottleneck, [3, 4, 23, 3], **kwargs)
| en | 0.799535 | #!/usr/bin/env python # -*- coding: utf-8 -*- resnet3d 3d resnet model (backbone for deeplabv3) Author: <NAME> (<EMAIL>) Created on: December 31, 2019 3x3 convolution with padding 1x1 convolution # Both self.conv2 and self.downsample layers downsample the input when stride != 1 # each element in the tuple indicates if we should replace # the 2x2 stride with a dilated convolution instead # Zero-initialize the last BN in each residual branch, # so that the residual branch starts with zeros, and each residual block behaves like an identity. # This improves the model by 0.2~0.3% according to https://arxiv.org/abs/1706.02677 # See note [TorchScript super()] | 2.261712 | 2 |
lab/refactoring/rename_method.py | Tanner-York-Make-School/SPD-2.31-Testing-and-Architecture | 0 | 6620569 | <reponame>Tanner-York-Make-School/SPD-2.31-Testing-and-Architecture<filename>lab/refactoring/rename_method.py
"""
By <NAME>
Rename Method
Reference: https://parade.com/1039985/marynliles/pick-up-lines/
"""
def calc_area_under_grapg(graph):
"""Calculate the area under the input graph."""
# bla bla bla.
pass
#####################
def get_largest_value(li):
"""Returns the largest value in the given list"""
m = li[0]
for value in li:
if value > m:
m = value
return m
li = [5, -1, 43, 32, 87, -100]
print(get_largest_value(li))
############################
def extract_words(sentence):
"""Extracts the words from a given sentence and returns them in an array"""
words = sentence[0:].split(' ')
return words
print(extract_words('If you were a vegetable, you’d be a ‘cute-cumber.'))
| """
By <NAME>
Rename Method
Reference: https://parade.com/1039985/marynliles/pick-up-lines/
"""
def calc_area_under_grapg(graph):
"""Calculate the area under the input graph."""
# bla bla bla.
pass
#####################
def get_largest_value(li):
"""Returns the largest value in the given list"""
m = li[0]
for value in li:
if value > m:
m = value
return m
li = [5, -1, 43, 32, 87, -100]
print(get_largest_value(li))
############################
def extract_words(sentence):
"""Extracts the words from a given sentence and returns them in an array"""
words = sentence[0:].split(' ')
return words
print(extract_words('If you were a vegetable, you’d be a ‘cute-cumber.')) | en | 0.50696 | By <NAME> Rename Method Reference: https://parade.com/1039985/marynliles/pick-up-lines/ Calculate the area under the input graph. # bla bla bla. ##################### Returns the largest value in the given list ############################ Extracts the words from a given sentence and returns them in an array | 3.813578 | 4 |
homeworks/ilya_nilov/hw05/level01.py | tgrx/Z22 | 0 | 6620570 | <filename>homeworks/ilya_nilov/hw05/level01.py
def summa(nmbr1, nmbr2):
return nmbr1 + nmbr2
| <filename>homeworks/ilya_nilov/hw05/level01.py
def summa(nmbr1, nmbr2):
return nmbr1 + nmbr2
| none | 1 | 2.189461 | 2 | |
python/258.add-digits.py | stavanmehta/leetcode | 0 | 6620571 | class Solution:
def addDigits(self, num: int) -> int:
| class Solution:
def addDigits(self, num: int) -> int:
| none | 1 | 2.135362 | 2 | |
tess/data/tess_file_format.py | LithiumSR/tess | 0 | 6620572 | <gh_stars>0
import os
import tempfile
import keras
from joblib import dump, load
class TessFileUtils:
@staticmethod
def save(filename, model):
model_tmp, schema_tmp, pca_tmp = [tempfile.NamedTemporaryFile(delete=False, prefix='tesstmp_') for x in
range(3)]
from tess.model.neural_model import TessNeuralModel
from tess.model.svr_model import TessSVRModel
if isinstance(model, TessNeuralModel):
mode = 0
model.model.save(model_tmp.name)
elif isinstance(model, TessSVRModel):
mode = 1
dump(model.model, model_tmp.name)
else:
raise AttributeError('Invalid model class')
dump(model.schema, schema_tmp.name)
if model.use_reduction:
dump(model.pca, pca_tmp.name)
tmp_files = [model_tmp, schema_tmp, pca_tmp]
with open(filename, 'wb') as fo:
fo.write(int.to_bytes(mode, 8, 'little'))
for el in tmp_files:
fo.write(int.to_bytes(os.stat(el.name).st_size, 8, 'little'))
for el in tmp_files:
fi = open(el.name, 'rb')
b = fi.read(256)
while b:
fo.write(b)
b = fi.read(256)
fi.close()
if isinstance(model, TessNeuralModel):
fo.write(int.to_bytes(model.epochs, 8, 'little'))
fo.write(int.to_bytes(model.batch_size, 8, 'little'))
for el in tmp_files:
os.remove(el.name)
@staticmethod
def load(filename, model):
with open(filename, 'rb') as fi:
mode, model_len, schema_len, pca_len = [int.from_bytes(fi.read(x), 'little') for x in [8, 8, 8, 8]]
from tess.model.neural_model import TessNeuralModel
from tess.model.svr_model import TessSVRModel
if (mode == 0 and not isinstance(model, TessNeuralModel)) or (
mode == 1 and not isinstance(model, TessSVRModel) or mode not in [0, 1]):
raise AttributeError("Model mismatch when restoring")
model.use_reduction = pca_len > 0
model_tmp, schema_tmp, pca_tmp = [tempfile.NamedTemporaryFile(delete=False, prefix='tesstmp_') for x
in range(3)]
tmp_files = [(model_len, model_tmp), (schema_len, schema_tmp), (pca_len, pca_tmp)]
for el in tmp_files:
with open(el[1].name, 'wb') as fo:
written_bytes = 0
while written_bytes < el[0]:
fo.write(fi.read(1))
written_bytes += 1
if isinstance(model, TessNeuralModel):
model.epochs = int.from_bytes(fi.read(8), 'little')
model.batch_size = int.from_bytes(fi.read(8), 'little')
model.model = keras.models.load_model(model_tmp)
elif mode == 1:
model.model = load(model_tmp)
model.schema = load(schema_tmp)
if model.use_reduction:
model.pca = load(pca_tmp)
for el in tmp_files:
os.remove(el[1].name)
| import os
import tempfile
import keras
from joblib import dump, load
class TessFileUtils:
@staticmethod
def save(filename, model):
model_tmp, schema_tmp, pca_tmp = [tempfile.NamedTemporaryFile(delete=False, prefix='tesstmp_') for x in
range(3)]
from tess.model.neural_model import TessNeuralModel
from tess.model.svr_model import TessSVRModel
if isinstance(model, TessNeuralModel):
mode = 0
model.model.save(model_tmp.name)
elif isinstance(model, TessSVRModel):
mode = 1
dump(model.model, model_tmp.name)
else:
raise AttributeError('Invalid model class')
dump(model.schema, schema_tmp.name)
if model.use_reduction:
dump(model.pca, pca_tmp.name)
tmp_files = [model_tmp, schema_tmp, pca_tmp]
with open(filename, 'wb') as fo:
fo.write(int.to_bytes(mode, 8, 'little'))
for el in tmp_files:
fo.write(int.to_bytes(os.stat(el.name).st_size, 8, 'little'))
for el in tmp_files:
fi = open(el.name, 'rb')
b = fi.read(256)
while b:
fo.write(b)
b = fi.read(256)
fi.close()
if isinstance(model, TessNeuralModel):
fo.write(int.to_bytes(model.epochs, 8, 'little'))
fo.write(int.to_bytes(model.batch_size, 8, 'little'))
for el in tmp_files:
os.remove(el.name)
@staticmethod
def load(filename, model):
with open(filename, 'rb') as fi:
mode, model_len, schema_len, pca_len = [int.from_bytes(fi.read(x), 'little') for x in [8, 8, 8, 8]]
from tess.model.neural_model import TessNeuralModel
from tess.model.svr_model import TessSVRModel
if (mode == 0 and not isinstance(model, TessNeuralModel)) or (
mode == 1 and not isinstance(model, TessSVRModel) or mode not in [0, 1]):
raise AttributeError("Model mismatch when restoring")
model.use_reduction = pca_len > 0
model_tmp, schema_tmp, pca_tmp = [tempfile.NamedTemporaryFile(delete=False, prefix='tesstmp_') for x
in range(3)]
tmp_files = [(model_len, model_tmp), (schema_len, schema_tmp), (pca_len, pca_tmp)]
for el in tmp_files:
with open(el[1].name, 'wb') as fo:
written_bytes = 0
while written_bytes < el[0]:
fo.write(fi.read(1))
written_bytes += 1
if isinstance(model, TessNeuralModel):
model.epochs = int.from_bytes(fi.read(8), 'little')
model.batch_size = int.from_bytes(fi.read(8), 'little')
model.model = keras.models.load_model(model_tmp)
elif mode == 1:
model.model = load(model_tmp)
model.schema = load(schema_tmp)
if model.use_reduction:
model.pca = load(pca_tmp)
for el in tmp_files:
os.remove(el[1].name) | none | 1 | 2.431567 | 2 | |
process_videos.py | NeelayS/pose_tracking | 0 | 6620573 | <reponame>NeelayS/pose_tracking
import os
from os.path import exists, join
import argparse
import json
from visualize import visualize
def generate_tracklets(results_list):
tracklets = {}
for frame in results_list:
person = frame["idx"]
if not person in tracklets.keys():
tracklets[person] = {}
keypoints = frame["keypoints"]
coordinate = [
(keypoints[3 * i], keypoints[3 * i + 1]) for i in range(len(keypoints) // 3)
]
confidence_score = [keypoints[3 * i + 2] for i in range(len(keypoints) // 3)]
overall_score = frame["score"]
if not "coordinates" in tracklets[person].keys():
tracklets[person]["coordinates"] = []
tracklets[person]["confidence_scores"] = []
tracklets[person]["overall_scores"] = []
tracklets[person]["coordinates"].append(coordinate)
tracklets[person]["confidence_scores"].append(confidence_score)
tracklets[person]["overall_scores"].append(overall_score)
for person in tracklets.keys():
tracklets[person]["avg_overall_score"] = sum(
tracklets[person]["overall_scores"]
) / len(tracklets[person]["overall_scores"])
return tracklets
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Script to generate tracklets from all videos in a directory"
)
parser.add_argument(
"--indir",
type=str,
required=True,
help="Should point to directory containing all the trimmed videos",
)
parser.add_argument(
"--outdir",
type=str,
required=True,
help="Location where all the output files should be saved",
)
parser.add_argument(
"--threshold",
type=float,
default=2.75,
help="Threshold score for filtering videos",
)
parser.add_argument(
"--visualize",
type=bool,
default=True,
help="Whether to the visualize the tracklets for videos which pass the filters",
)
parser.add_argument(
"--min_time_fraction",
type=float,
default=0.2,
help="Min fraction of time the person must be present in the video to be considered",
)
parser.add_argument(
"--n_people",
type=int,
default=5,
help="Top k people to be stored for the videos on which performance is suitable",
)
parser.add_argument(
"--n_cat_videos",
type=int,
default=5,
help="No. of videos of each category required",
)
parser.add_argument(
"--detbatch", type=int, default=5, help="detection batch size PER GPU"
)
parser.add_argument(
"--posebatch",
type=int,
default=10,
help="pose estimation maximum batch size PER GPU",
)
parser.add_argument(
"--gpus",
type=str,
dest="gpus",
default="0",
help="choose which cuda device to use by index and input comma to use multi gpus, e.g. 0,1,2,3. (input -1 for cpu only)",
)
parser.add_argument(
"--qsize",
type=int,
dest="qsize",
default=32,
help="the length of result buffer, where reducing it will lower requirement of cpu memory",
)
args = parser.parse_args()
ckpt = "pretrained_models/fast_421_res152_256x192.pth"
cfg = "configs/coco/resnet/256x192_res152_lr1e-3_1x-duc.yaml"
if not exists(args.outdir):
# print("The output directory doesn't exist. Creating it.")
for name in ["AP_results", "tracklets", "videos"]:
os.makedirs(join(args.outdir, name), exist_ok=True)
os.mkdir(join(args.outdir, "AP_results", "all"))
os.mkdir(join(args.outdir, "AP_results", "filtered"))
for category in os.listdir(args.indir):
if not exists(join(args.outdir, "tracklets", category)):
os.mkdir(join(args.outdir, "tracklets", category))
if not exists(join(args.outdir, "videos", category)):
os.mkdir(join(args.outdir, "videos", category))
if not exists(join(args.outdir, "AP_results", "all", category)):
os.makedirs(join(args.outdir, "AP_results", "all", category))
if not exists(join(args.outdir, "AP_results", "filtered", category)):
os.makedirs(join(args.outdir, "AP_results", "filtered", category))
category_count = 0
for video in os.listdir(join(args.indir, category)):
if exists(
join(args.outdir, "AP_results", "all", category, video[:-4] + ".json")
):
print(
f"The results for video {category}/{video[:-4]} exist already. Moving to next\n"
)
continue
if category_count == args.n_cat_videos:
break
video_path = join(args.indir, category, video)
results_path = join(args.outdir, "AP_results", "all", category)
print(f"Processing video {category}/{video}")
command = f"python scripts/demo_inference.py --checkpoint {ckpt} --cfg {cfg} --video {video_path} --outdir {results_path} --gpus {args.gpus} --detbatch {args.detbatch} --posebatch {args.posebatch} --qsize {args.qsize} --pose_track"
os.system(command)
try:
file_handle = open(join(results_path, "alphapose-results.json"))
except:
print("There was a problem with processing this video. Moving to next")
continue
results_list = json.load(file_handle)
file_handle.close()
tracklets = generate_tracklets(results_list)
n_frames = len(results_list)
min_frames = int(n_frames * args.min_time_fraction)
filtered_persons = {
person: tracklets[person]["avg_overall_score"]
for person in tracklets.keys()
if len(tracklets[person]["overall_scores"]) > min_frames
}
if not filtered_persons or len(filtered_persons.keys()) < 2:
print(
"This video is not suitable to be a part of the dataset. Moving to next\n"
)
os.rename(
join(results_path, "alphapose-results.json"),
join(results_path, video[:-4] + ".json"),
)
continue
sorted_filtered_persons = {
person: score
for person, score in sorted(
filtered_persons.items(), key=lambda item: item[1], reverse=True
)
}
is_video_suitable = 1
for person in list(sorted_filtered_persons.keys())[:2]:
if not sorted_filtered_persons[person] >= args.threshold:
is_video_suitable = 0
break
if is_video_suitable:
print("This video is suitable to be a part of the dataset\n")
try:
person_ids = list(sorted_filtered_persons.keys())[: args.n_people]
except:
person_ids = sorted_filtered_persons.keys()
filtered_tracklets = {
person: tracklet
for person, tracklet in tracklets.items()
if person in person_ids
}
filtered_results_list = [
person for person in results_list if person["idx"] in person_ids
]
tracklets_json = json.dumps(filtered_tracklets)
tracklets_file_handle = open(
join(
args.outdir,
"tracklets",
category,
"tracklets_" + video[:-4] + ".json",
),
"w",
)
tracklets_file_handle.write(tracklets_json)
tracklets_file_handle.close()
results_json = json.dumps(filtered_results_list)
results_file_handle = open(
join(
args.outdir,
"AP_results",
"filtered",
category,
"filtered_" + video[:-4] + ".json",
),
"w",
)
results_file_handle.write(results_json)
results_file_handle.close()
if args.visualize:
visualize(
filtered_results_list,
video_path,
join(args.outdir, "videos", category, video[:-4] + ".mp4"),
)
category_count += 1
else:
print(
"This video is not suitable to be a part of the dataset. Moving to next\n"
)
os.rename(
join(results_path, "alphapose-results.json"),
join(results_path, video[:-4] + ".json"),
)
| import os
from os.path import exists, join
import argparse
import json
from visualize import visualize
def generate_tracklets(results_list):
tracklets = {}
for frame in results_list:
person = frame["idx"]
if not person in tracklets.keys():
tracklets[person] = {}
keypoints = frame["keypoints"]
coordinate = [
(keypoints[3 * i], keypoints[3 * i + 1]) for i in range(len(keypoints) // 3)
]
confidence_score = [keypoints[3 * i + 2] for i in range(len(keypoints) // 3)]
overall_score = frame["score"]
if not "coordinates" in tracklets[person].keys():
tracklets[person]["coordinates"] = []
tracklets[person]["confidence_scores"] = []
tracklets[person]["overall_scores"] = []
tracklets[person]["coordinates"].append(coordinate)
tracklets[person]["confidence_scores"].append(confidence_score)
tracklets[person]["overall_scores"].append(overall_score)
for person in tracklets.keys():
tracklets[person]["avg_overall_score"] = sum(
tracklets[person]["overall_scores"]
) / len(tracklets[person]["overall_scores"])
return tracklets
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Script to generate tracklets from all videos in a directory"
)
parser.add_argument(
"--indir",
type=str,
required=True,
help="Should point to directory containing all the trimmed videos",
)
parser.add_argument(
"--outdir",
type=str,
required=True,
help="Location where all the output files should be saved",
)
parser.add_argument(
"--threshold",
type=float,
default=2.75,
help="Threshold score for filtering videos",
)
parser.add_argument(
"--visualize",
type=bool,
default=True,
help="Whether to the visualize the tracklets for videos which pass the filters",
)
parser.add_argument(
"--min_time_fraction",
type=float,
default=0.2,
help="Min fraction of time the person must be present in the video to be considered",
)
parser.add_argument(
"--n_people",
type=int,
default=5,
help="Top k people to be stored for the videos on which performance is suitable",
)
parser.add_argument(
"--n_cat_videos",
type=int,
default=5,
help="No. of videos of each category required",
)
parser.add_argument(
"--detbatch", type=int, default=5, help="detection batch size PER GPU"
)
parser.add_argument(
"--posebatch",
type=int,
default=10,
help="pose estimation maximum batch size PER GPU",
)
parser.add_argument(
"--gpus",
type=str,
dest="gpus",
default="0",
help="choose which cuda device to use by index and input comma to use multi gpus, e.g. 0,1,2,3. (input -1 for cpu only)",
)
parser.add_argument(
"--qsize",
type=int,
dest="qsize",
default=32,
help="the length of result buffer, where reducing it will lower requirement of cpu memory",
)
args = parser.parse_args()
ckpt = "pretrained_models/fast_421_res152_256x192.pth"
cfg = "configs/coco/resnet/256x192_res152_lr1e-3_1x-duc.yaml"
if not exists(args.outdir):
# print("The output directory doesn't exist. Creating it.")
for name in ["AP_results", "tracklets", "videos"]:
os.makedirs(join(args.outdir, name), exist_ok=True)
os.mkdir(join(args.outdir, "AP_results", "all"))
os.mkdir(join(args.outdir, "AP_results", "filtered"))
for category in os.listdir(args.indir):
if not exists(join(args.outdir, "tracklets", category)):
os.mkdir(join(args.outdir, "tracklets", category))
if not exists(join(args.outdir, "videos", category)):
os.mkdir(join(args.outdir, "videos", category))
if not exists(join(args.outdir, "AP_results", "all", category)):
os.makedirs(join(args.outdir, "AP_results", "all", category))
if not exists(join(args.outdir, "AP_results", "filtered", category)):
os.makedirs(join(args.outdir, "AP_results", "filtered", category))
category_count = 0
for video in os.listdir(join(args.indir, category)):
if exists(
join(args.outdir, "AP_results", "all", category, video[:-4] + ".json")
):
print(
f"The results for video {category}/{video[:-4]} exist already. Moving to next\n"
)
continue
if category_count == args.n_cat_videos:
break
video_path = join(args.indir, category, video)
results_path = join(args.outdir, "AP_results", "all", category)
print(f"Processing video {category}/{video}")
command = f"python scripts/demo_inference.py --checkpoint {ckpt} --cfg {cfg} --video {video_path} --outdir {results_path} --gpus {args.gpus} --detbatch {args.detbatch} --posebatch {args.posebatch} --qsize {args.qsize} --pose_track"
os.system(command)
try:
file_handle = open(join(results_path, "alphapose-results.json"))
except:
print("There was a problem with processing this video. Moving to next")
continue
results_list = json.load(file_handle)
file_handle.close()
tracklets = generate_tracklets(results_list)
n_frames = len(results_list)
min_frames = int(n_frames * args.min_time_fraction)
filtered_persons = {
person: tracklets[person]["avg_overall_score"]
for person in tracklets.keys()
if len(tracklets[person]["overall_scores"]) > min_frames
}
if not filtered_persons or len(filtered_persons.keys()) < 2:
print(
"This video is not suitable to be a part of the dataset. Moving to next\n"
)
os.rename(
join(results_path, "alphapose-results.json"),
join(results_path, video[:-4] + ".json"),
)
continue
sorted_filtered_persons = {
person: score
for person, score in sorted(
filtered_persons.items(), key=lambda item: item[1], reverse=True
)
}
is_video_suitable = 1
for person in list(sorted_filtered_persons.keys())[:2]:
if not sorted_filtered_persons[person] >= args.threshold:
is_video_suitable = 0
break
if is_video_suitable:
print("This video is suitable to be a part of the dataset\n")
try:
person_ids = list(sorted_filtered_persons.keys())[: args.n_people]
except:
person_ids = sorted_filtered_persons.keys()
filtered_tracklets = {
person: tracklet
for person, tracklet in tracklets.items()
if person in person_ids
}
filtered_results_list = [
person for person in results_list if person["idx"] in person_ids
]
tracklets_json = json.dumps(filtered_tracklets)
tracklets_file_handle = open(
join(
args.outdir,
"tracklets",
category,
"tracklets_" + video[:-4] + ".json",
),
"w",
)
tracklets_file_handle.write(tracklets_json)
tracklets_file_handle.close()
results_json = json.dumps(filtered_results_list)
results_file_handle = open(
join(
args.outdir,
"AP_results",
"filtered",
category,
"filtered_" + video[:-4] + ".json",
),
"w",
)
results_file_handle.write(results_json)
results_file_handle.close()
if args.visualize:
visualize(
filtered_results_list,
video_path,
join(args.outdir, "videos", category, video[:-4] + ".mp4"),
)
category_count += 1
else:
print(
"This video is not suitable to be a part of the dataset. Moving to next\n"
)
os.rename(
join(results_path, "alphapose-results.json"),
join(results_path, video[:-4] + ".json"),
) | en | 0.90069 | # print("The output directory doesn't exist. Creating it.") | 2.731653 | 3 |
web/blueprints/Login.py | arashmjr/ClubHouseFollowers | 0 | 6620574 | <filename>web/blueprints/Login.py<gh_stars>0
from flask import Blueprint
from flask import request
from seviceLayer.core.ServiceProvider import ServiceProvider
from web.dtos.BaseResponse import BaseError, BaseResponse
from web.utils.Localization import MessageIds
from flask import jsonify
from flask_api import status
Login = Blueprint('Login', __name__)
@Login.route('/Login', methods=['POST'])
def login():
json = request.get_json()
try:
service = ServiceProvider().make_login_service()
token = service.login_user(json)
response = BaseResponse({"access token": token}, True, MessageIds.SUCCESS)
return jsonify(response.serialize()), status.HTTP_201_CREATED
except ValueError:
response = BaseError(MessageIds.ERROR_BAD_JSON)
return jsonify(response.serialize()), status.HTTP_400_BAD_REQUEST
| <filename>web/blueprints/Login.py<gh_stars>0
from flask import Blueprint
from flask import request
from seviceLayer.core.ServiceProvider import ServiceProvider
from web.dtos.BaseResponse import BaseError, BaseResponse
from web.utils.Localization import MessageIds
from flask import jsonify
from flask_api import status
Login = Blueprint('Login', __name__)
@Login.route('/Login', methods=['POST'])
def login():
json = request.get_json()
try:
service = ServiceProvider().make_login_service()
token = service.login_user(json)
response = BaseResponse({"access token": token}, True, MessageIds.SUCCESS)
return jsonify(response.serialize()), status.HTTP_201_CREATED
except ValueError:
response = BaseError(MessageIds.ERROR_BAD_JSON)
return jsonify(response.serialize()), status.HTTP_400_BAD_REQUEST
| none | 1 | 2.484155 | 2 | |
PySRCG/src/GenModes/points.py | apampuch/PySRCG | 0 | 6620575 | from abc import ABC
from src.GenModes.gen_mode import GenMode
class Points(GenMode, ABC):
def __init__(self):
super().__init__()
self.starting_skills_max = 6
def get_generated_value(self, key):
pass
def update_karma_label(self, tab):
pass
def setup_ui_elements(self):
pass
def serialize(self):
pass
def update_total(self, amount, key):
pass
def point_purchase_allowed(self, amount, key):
"""Ignore key since we draw from the same pool."""
pass | from abc import ABC
from src.GenModes.gen_mode import GenMode
class Points(GenMode, ABC):
def __init__(self):
super().__init__()
self.starting_skills_max = 6
def get_generated_value(self, key):
pass
def update_karma_label(self, tab):
pass
def setup_ui_elements(self):
pass
def serialize(self):
pass
def update_total(self, amount, key):
pass
def point_purchase_allowed(self, amount, key):
"""Ignore key since we draw from the same pool."""
pass | en | 0.953159 | Ignore key since we draw from the same pool. | 2.418746 | 2 |
test.py | okutani-t/python-code | 0 | 6620576 | <reponame>okutani-t/python-code
# -*- coding: utf-8 -*-
import random
i = random.randint(1,101)
if i<50:
print"これは50より小さい"+ str(i) + "です。残念！"
else:
print"50より大きい"+ str(i) + "です。やったね！"
| # -*- coding: utf-8 -*-
import random
i = random.randint(1,101)
if i<50:
print"これは50より小さい"+ str(i) + "です。残念！"
else:
print"50より大きい"+ str(i) + "です。やったね！" | en | 0.769321 | # -*- coding: utf-8 -*- | 3.431012 | 3 |
pyogp/lib/base/helpers.py | grobertson/PyOGP.lib.Base | 0 | 6620577 | <reponame>grobertson/PyOGP.lib.Base
"""
Contributors can be viewed at:
http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/trunk/CONTRIBUTORS.txt
$LicenseInfo:firstyear=2008&license=apachev2$
Copyright 2009, Linden Research, Inc.
Licensed under the Apache License, Version 2.0.
You may obtain a copy of the License at:
http://www.apache.org/licenses/LICENSE-2.0
or in
http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/LICENSE.txt
$/LicenseInfo$
"""
# standard python libs
from logging import getLogger
import time
import struct
import math
# related
from llbase import llsd
try:
from eventlet import api as eventlet
except ImportError:
import eventlet
# pyogp
from pyogp.lib.base.exc import DataParsingError, DeserializationFailed
# initialize loggin
logger = getLogger('...utilities.helpers')
class Helpers(object):
""" contains useful helper functions """
@staticmethod
def bytes_to_hex(data):
""" converts bytes to hex format """
#from binascii import hexlify
#return hex_string
#hex_string = hexlify(data)
return ''.join(["%02X " % ord(x) for x in data]).strip()
@staticmethod
def bytes_to_ascii(data):
" converts bytes to ascii format "
from binascii import b2a_uu
ascii_string = b2a_uu(data)
return ascii_string
@staticmethod
def hex_to_ascii(data):
" converts bytes to ascii format "
from binascii import unhexlify
try:
ascii_string = unhexlify(data)
except TypeError, error:
raise DataParsingError('hex_to_ascii failure: \'%s\': processing data: \'%s\'' % (error, data))
return ascii_string
@staticmethod
def bytes_to_base64(data):
" converts bytes to ascii format "
from binascii import b2a_base64
base64_string = b2a_base64(data)
return base64_string
@staticmethod
def packed_u16_to_float(bytes, offset, lower, upper):
""" Extract float packed as u16 in a byte buffer """
U16MAX = 65535
OOU16MAX = 1.0/U16MAX
u16 = struct.unpack('<H', bytes[offset:offset+2])[0]
val = u16 * OOU16MAX
delta = upper - lower
val *= delta
val += lower
max_error = delta * OOU16MAX
if math.fabs(val) < max_error:
val = 0.0
return val
@staticmethod
def packed_u8_to_float(bytes, offset, lower, upper):
""" Extract float packed as u8 in a byte buffer """
U8MAX = 255
OOU8MAX = 1.0/U8MAX
u8 = struct.unpack('<B', bytes[offset:offset+1])[0]
val = u8 * OOU8MAX
delta = upper - lower
val *= delta
val += lower
max_error = delta * OOU8MAX
if math.fabs(val) < max_error:
val = 0.0
return val
@staticmethod
def pack_quaternion_to_vector3(quaternion):
""" pack a normalized quaternion (tuple) into a vector3 (tuple) """
if quaternion[3] >= 0:
return (quaternion[0], quaternion[1], quaternion[2])
else:
return (-quaternion[0], -quaternion[1], -quaternion[2])
@staticmethod
def int_to_bytes(data):
"""
converts an int to a string of bytes
"""
return struct.pack('BBBB',
data % 256,
(data >> 8) % 256,
(data >> 16) % 256,
(data >> 24) % 256)
# ~~~~~~~~~
# Callbacks
# ~~~~~~~~~
@staticmethod
def log_packet(packet, _object):
""" default logging function for packets """
logger.info("Object %s is monitoring packet type %s: \n%s" % (type(_object), packet.name, packet.data()))
@staticmethod
def log_event_queue_data(data, _object):
""" default logging function for event queue data events """
logger.info("Object %s is monitoring event queue data event %s: \n%s" % (type(_object), data.name, data.__dict__))
@staticmethod
def null_packet_handler(packet, _object):
""" just a null event handler for watching aka fully parsing specific packets """
pass
class ListLLSDSerializer(object):
"""adapter for serializing a list to LLSD
An example:
>>> d=['ChatSessionRequest', 'CopyInventoryFromNotecard']
>>> serializer = ListLLSDSerializer(d)
>>> serializer.serialize()
'<?xml version="1.0" ?><llsd><array><string>ChatSessionRequest</string><string>CopyInventoryFromNotecard</string></array></llsd>'
>>> serializer.content_type
'application/llsd+xml'
"""
def __init__(self, context):
self.context = context
def serialize(self):
"""convert the payload to LLSD"""
return llsd.format_xml(self.context)
@property
def content_type(self):
"""return the content type of this serializer"""
return "application/llsd+xml"
class DictLLSDSerializer(object):
"""adapter for serializing a dictionary to LLSD
An example:
>>> d={'foo':'bar', 'test':1234}
>>> serializer = DictLLSDSerializer(d)
>>> serializer.serialize()
'<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>'
>>> serializer.content_type
'application/llsd+xml'
"""
def __init__(self, context):
self.context = context
def serialize(self):
"""convert the payload to LLSD"""
return llsd.format_xml(self.context)
@property
def content_type(self):
"""return the content type of this serializer"""
return "application/llsd+xml"
class LLSDDeserializer(object):
"""utility for deserializing LLSD data
The deserialization component is defined as a utility because the input
data can be a string or a file. It might be possible to define this as
an adapter on a string but a string is too generic for this. So that's
why it is a utility.
You can use it like this:
>>> s='<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>'
We use queryUtility because this returns None instead of an exception
when a utility is not registered. We use the content type we received
as the name of the utility. Another option would of course be to subclas
string to some LLSDString class and use an adapter. We then would need some
factory for generating the LLSDString class from whatever came back from
the HTTP call.
So here is how you use that utility:
>>> deserializer = LLSDDeserializer()
>>> llsd = deserializer.deserialize(s)
>>> llsd
{'test': 1234, 'foo': 'bar'}
We can also test this with some non-LLSD string:
>>> llsd = deserializer.deserialize_string('mumpitz') # this is not LLSD
Traceback (most recent call last):
...
DeserializationFailed: deserialization failed for 'mumpitz', reason: 'invalid token at index 0: 109'
>>> llsd = deserializer.deserialize_string('barfoo')
Traceback (most recent call last):
...
DeserializationFailed: deserialization failed for 'barfoo', reason: 'random horrible binary format not supported'
"""
def deserialize(self, data):
""" convenience class to handle a variety of inputs """
if type(data) == str:
return self.deserialize_string(data)
# won't handle another case until we need to
def deserialize_string(self, data):
""" deserialize a string """
try:
r = llsd.parse(data)
except llsd.LLSDParseError, e:
raise DeserializationFailed(data, str(e))
if r==False:
raise DeserializationFailed(data, 'result was False')
return r
def deserialize_file(self, fp):
""" deserialize a file """
data = fp.read()
return self.deserialize_string(data)
class Wait(object):
""" a simple timer that blocks a calling routine for the specified number of seconds
done since we were writing timing loops in test scripts repeatedly
returns True when it's done
"""
def __init__(self, duration):
self.duration = int(duration)
# let's be nice and enabled a kill switch
self.enabled = False
self.run()
def run(self):
now = time.time()
start = now
self.enabled = True
while self.enabled and now - start < self.duration:
try:
eventlet.sleep()
now = time.time()
except AssertionError:
pass
return True
def stop(self):
self.enabled = False
| """
Contributors can be viewed at:
http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/trunk/CONTRIBUTORS.txt
$LicenseInfo:firstyear=2008&license=apachev2$
Copyright 2009, Linden Research, Inc.
Licensed under the Apache License, Version 2.0.
You may obtain a copy of the License at:
http://www.apache.org/licenses/LICENSE-2.0
or in
http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/LICENSE.txt
$/LicenseInfo$
"""
# standard python libs
from logging import getLogger
import time
import struct
import math
# related
from llbase import llsd
try:
from eventlet import api as eventlet
except ImportError:
import eventlet
# pyogp
from pyogp.lib.base.exc import DataParsingError, DeserializationFailed
# initialize loggin
logger = getLogger('...utilities.helpers')
class Helpers(object):
""" contains useful helper functions """
@staticmethod
def bytes_to_hex(data):
""" converts bytes to hex format """
#from binascii import hexlify
#return hex_string
#hex_string = hexlify(data)
return ''.join(["%02X " % ord(x) for x in data]).strip()
@staticmethod
def bytes_to_ascii(data):
" converts bytes to ascii format "
from binascii import b2a_uu
ascii_string = b2a_uu(data)
return ascii_string
@staticmethod
def hex_to_ascii(data):
" converts bytes to ascii format "
from binascii import unhexlify
try:
ascii_string = unhexlify(data)
except TypeError, error:
raise DataParsingError('hex_to_ascii failure: \'%s\': processing data: \'%s\'' % (error, data))
return ascii_string
@staticmethod
def bytes_to_base64(data):
" converts bytes to ascii format "
from binascii import b2a_base64
base64_string = b2a_base64(data)
return base64_string
@staticmethod
def packed_u16_to_float(bytes, offset, lower, upper):
""" Extract float packed as u16 in a byte buffer """
U16MAX = 65535
OOU16MAX = 1.0/U16MAX
u16 = struct.unpack('<H', bytes[offset:offset+2])[0]
val = u16 * OOU16MAX
delta = upper - lower
val *= delta
val += lower
max_error = delta * OOU16MAX
if math.fabs(val) < max_error:
val = 0.0
return val
@staticmethod
def packed_u8_to_float(bytes, offset, lower, upper):
""" Extract float packed as u8 in a byte buffer """
U8MAX = 255
OOU8MAX = 1.0/U8MAX
u8 = struct.unpack('<B', bytes[offset:offset+1])[0]
val = u8 * OOU8MAX
delta = upper - lower
val *= delta
val += lower
max_error = delta * OOU8MAX
if math.fabs(val) < max_error:
val = 0.0
return val
@staticmethod
def pack_quaternion_to_vector3(quaternion):
""" pack a normalized quaternion (tuple) into a vector3 (tuple) """
if quaternion[3] >= 0:
return (quaternion[0], quaternion[1], quaternion[2])
else:
return (-quaternion[0], -quaternion[1], -quaternion[2])
@staticmethod
def int_to_bytes(data):
"""
converts an int to a string of bytes
"""
return struct.pack('BBBB',
data % 256,
(data >> 8) % 256,
(data >> 16) % 256,
(data >> 24) % 256)
# ~~~~~~~~~
# Callbacks
# ~~~~~~~~~
@staticmethod
def log_packet(packet, _object):
""" default logging function for packets """
logger.info("Object %s is monitoring packet type %s: \n%s" % (type(_object), packet.name, packet.data()))
@staticmethod
def log_event_queue_data(data, _object):
""" default logging function for event queue data events """
logger.info("Object %s is monitoring event queue data event %s: \n%s" % (type(_object), data.name, data.__dict__))
@staticmethod
def null_packet_handler(packet, _object):
""" just a null event handler for watching aka fully parsing specific packets """
pass
class ListLLSDSerializer(object):
"""adapter for serializing a list to LLSD
An example:
>>> d=['ChatSessionRequest', 'CopyInventoryFromNotecard']
>>> serializer = ListLLSDSerializer(d)
>>> serializer.serialize()
'<?xml version="1.0" ?><llsd><array><string>ChatSessionRequest</string><string>CopyInventoryFromNotecard</string></array></llsd>'
>>> serializer.content_type
'application/llsd+xml'
"""
def __init__(self, context):
self.context = context
def serialize(self):
"""convert the payload to LLSD"""
return llsd.format_xml(self.context)
@property
def content_type(self):
"""return the content type of this serializer"""
return "application/llsd+xml"
class DictLLSDSerializer(object):
"""adapter for serializing a dictionary to LLSD
An example:
>>> d={'foo':'bar', 'test':1234}
>>> serializer = DictLLSDSerializer(d)
>>> serializer.serialize()
'<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>'
>>> serializer.content_type
'application/llsd+xml'
"""
def __init__(self, context):
self.context = context
def serialize(self):
"""convert the payload to LLSD"""
return llsd.format_xml(self.context)
@property
def content_type(self):
"""return the content type of this serializer"""
return "application/llsd+xml"
class LLSDDeserializer(object):
"""utility for deserializing LLSD data
The deserialization component is defined as a utility because the input
data can be a string or a file. It might be possible to define this as
an adapter on a string but a string is too generic for this. So that's
why it is a utility.
You can use it like this:
>>> s='<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>'
We use queryUtility because this returns None instead of an exception
when a utility is not registered. We use the content type we received
as the name of the utility. Another option would of course be to subclas
string to some LLSDString class and use an adapter. We then would need some
factory for generating the LLSDString class from whatever came back from
the HTTP call.
So here is how you use that utility:
>>> deserializer = LLSDDeserializer()
>>> llsd = deserializer.deserialize(s)
>>> llsd
{'test': 1234, 'foo': 'bar'}
We can also test this with some non-LLSD string:
>>> llsd = deserializer.deserialize_string('mumpitz') # this is not LLSD
Traceback (most recent call last):
...
DeserializationFailed: deserialization failed for 'mumpitz', reason: 'invalid token at index 0: 109'
>>> llsd = deserializer.deserialize_string('barfoo')
Traceback (most recent call last):
...
DeserializationFailed: deserialization failed for 'barfoo', reason: 'random horrible binary format not supported'
"""
def deserialize(self, data):
""" convenience class to handle a variety of inputs """
if type(data) == str:
return self.deserialize_string(data)
# won't handle another case until we need to
def deserialize_string(self, data):
""" deserialize a string """
try:
r = llsd.parse(data)
except llsd.LLSDParseError, e:
raise DeserializationFailed(data, str(e))
if r==False:
raise DeserializationFailed(data, 'result was False')
return r
def deserialize_file(self, fp):
""" deserialize a file """
data = fp.read()
return self.deserialize_string(data)
class Wait(object):
""" a simple timer that blocks a calling routine for the specified number of seconds
done since we were writing timing loops in test scripts repeatedly
returns True when it's done
"""
def __init__(self, duration):
self.duration = int(duration)
# let's be nice and enabled a kill switch
self.enabled = False
self.run()
def run(self):
now = time.time()
start = now
self.enabled = True
while self.enabled and now - start < self.duration:
try:
eventlet.sleep()
now = time.time()
except AssertionError:
pass
return True
def stop(self):
self.enabled = False | en | 0.651251 | Contributors can be viewed at: http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/trunk/CONTRIBUTORS.txt $LicenseInfo:firstyear=2008&license=apachev2$ Copyright 2009, Linden Research, Inc. Licensed under the Apache License, Version 2.0. You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0 or in http://svn.secondlife.com/svn/linden/projects/2008/pyogp/lib/base/LICENSE.txt $/LicenseInfo$ # standard python libs # related # pyogp # initialize loggin contains useful helper functions converts bytes to hex format #from binascii import hexlify #return hex_string #hex_string = hexlify(data) Extract float packed as u16 in a byte buffer Extract float packed as u8 in a byte buffer pack a normalized quaternion (tuple) into a vector3 (tuple) converts an int to a string of bytes # ~~~~~~~~~ # Callbacks # ~~~~~~~~~ default logging function for packets default logging function for event queue data events just a null event handler for watching aka fully parsing specific packets adapter for serializing a list to LLSD An example: >>> d=['ChatSessionRequest', 'CopyInventoryFromNotecard'] >>> serializer = ListLLSDSerializer(d) >>> serializer.serialize() '<?xml version="1.0" ?><llsd><array><string>ChatSessionRequest</string><string>CopyInventoryFromNotecard</string></array></llsd>' >>> serializer.content_type 'application/llsd+xml' convert the payload to LLSD return the content type of this serializer adapter for serializing a dictionary to LLSD An example: >>> d={'foo':'bar', 'test':1234} >>> serializer = DictLLSDSerializer(d) >>> serializer.serialize() '<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>' >>> serializer.content_type 'application/llsd+xml' convert the payload to LLSD return the content type of this serializer utility for deserializing LLSD data The deserialization component is defined as a utility because the input data can be a string or a file. It might be possible to define this as an adapter on a string but a string is too generic for this. So that's why it is a utility. You can use it like this: >>> s='<?xml version="1.0" ?><llsd><map><key>test</key><integer>1234</integer><key>foo</key><string>bar</string></map></llsd>' We use queryUtility because this returns None instead of an exception when a utility is not registered. We use the content type we received as the name of the utility. Another option would of course be to subclas string to some LLSDString class and use an adapter. We then would need some factory for generating the LLSDString class from whatever came back from the HTTP call. So here is how you use that utility: >>> deserializer = LLSDDeserializer() >>> llsd = deserializer.deserialize(s) >>> llsd {'test': 1234, 'foo': 'bar'} We can also test this with some non-LLSD string: >>> llsd = deserializer.deserialize_string('mumpitz') # this is not LLSD Traceback (most recent call last): ... DeserializationFailed: deserialization failed for 'mumpitz', reason: 'invalid token at index 0: 109' >>> llsd = deserializer.deserialize_string('barfoo') Traceback (most recent call last): ... DeserializationFailed: deserialization failed for 'barfoo', reason: 'random horrible binary format not supported' convenience class to handle a variety of inputs # won't handle another case until we need to deserialize a string deserialize a file a simple timer that blocks a calling routine for the specified number of seconds done since we were writing timing loops in test scripts repeatedly returns True when it's done # let's be nice and enabled a kill switch | 2.071093 | 2 |
osgar/drivers/test_rosmsg.py | robotika/osgar | 12 | 6620578 | <gh_stars>10-100
import unittest
from unittest.mock import MagicMock
from osgar.drivers.rosmsg import (ROSMsgParser, parse_volatile, parse_bucket, parse_topic)
class ROSMsgParserTest(unittest.TestCase):
def test_parse_volatile(self):
data = b"<\x00\x00\x00\x8c\x00\x00\x009\x00\x00\x00\x00'\xb9)\x17\x00\x00\x00" + \
b"scout_1/volatile_sensor\x08\x00\x00\x00methanol\n\x00\x00\x00\x01\xfb\xde`?"
self.assertEqual(parse_volatile(data), ['methanol', 0.8784024119377136, 10])
def test_parse_bucket(self):
data = b'\x16\x00\x00\x00\n\x00\x00\x00sulfur_dio\x1b\x00\x00\x00\xd3\xa7\xabA'
self.assertEqual(parse_bucket(data), ['sulfur_dio', 27, 21.456945419311523])
def test_parse_bin(self):
data = b'\x82\x00\x00\x00\x03\x00\x00\x00ice\x06\x00\x00\x00ethene\x07\x00\x00\x00methane\x0b\x00\x00\x00carbon_mono\n\x00\x00\x00carbon_dio\x07\x00\x00\x00ammonia\x0c\x00\x00\x00hydrogen_sul\n\x00\x00\x00sulfur_dio\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
self.assertEqual(parse_topic('srcp2_msgs/HaulerMsg', data), [['ice', 'ethene', 'methane', 'carbon_mono', 'carbon_dio', 'ammonia', 'hydrogen_sul', 'sulfur_dio'], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]])
def test_parse_score_qual2(self):
data = b'\x87\x00\x00\x00\x03\x00\x00\x00ice\x06\x00\x00\x00ethene\x07\x00\x00\x00methane' + \
b'\x08\x00\x00\x00carbon_mono\n\x00\x00\x00carbon_dio\x07\x00\x00\x00ammonia\x0c\x00\x00\x00' + \
b'hydrogen_sul\n\x00\x00\x00sulfur_dio\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' + \
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' + \
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00'
self.assertEqual(parse_topic('srcp2_msgs/Qual2ScoringMsg', data), [0, 0])
def test_radio(self):
data = b'radio X30F60R [0, 100, 30]\n'
bus = MagicMock()
r = ROSMsgParser(config={}, bus=bus)
r.slot_raw(timestamp=None, data=data)
bus.publish.assert_called_with('radio', [b'X30F60R', b'[0, 100, 30]\n'])
def test_publish_desired_speed(self):
data = b'\x08\x00\x00\x00\x02\x00\x00\x00\x00\x06\x81\x14' # clock as 8 bytes
bus = MagicMock()
r = ROSMsgParser(config={}, bus=bus)
r.slot_raw(timestamp=None, data=data)
bus.publish.assert_called_with('sim_time_sec', 2)
clock_data = b'\x08\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' # clock 3s
r.slot_raw(timestamp=None, data=clock_data)
bus.publish.assert_called_with('sim_time_sec', 3) # initially desired speed is None -> no cmd
r.slot_desired_speed(timestamp=None, data=[0, 0])
r.slot_raw(timestamp=None, data=clock_data)
# ... asserting that the last call has been made in a particular way
bus.publish.assert_called_with('cmd', b'cmd_vel 0.000000 0.000000')
# after update from 3D desired speed only extended cmd_vel_3d should be used
r.slot_desired_speed_3d(timestamp=None, data=[[1, 2, 3], [4, 5, 6]])
r.slot_raw(timestamp=None, data=clock_data)
bus.publish.assert_called_with('cmd', b'cmd_vel_3d 1.000000 2.000000 3.000000 4.000000 5.000000 6.000000')
def test_publish_undefined_desired_speed(self):
# for the drone it is important not to send any command until the very first desired speed is received
pass
# vim: expandtab sw=4 ts=4
| import unittest
from unittest.mock import MagicMock
from osgar.drivers.rosmsg import (ROSMsgParser, parse_volatile, parse_bucket, parse_topic)
class ROSMsgParserTest(unittest.TestCase):
def test_parse_volatile(self):
data = b"<\x00\x00\x00\x8c\x00\x00\x009\x00\x00\x00\x00'\xb9)\x17\x00\x00\x00" + \
b"scout_1/volatile_sensor\x08\x00\x00\x00methanol\n\x00\x00\x00\x01\xfb\xde`?"
self.assertEqual(parse_volatile(data), ['methanol', 0.8784024119377136, 10])
def test_parse_bucket(self):
data = b'\x16\x00\x00\x00\n\x00\x00\x00sulfur_dio\x1b\x00\x00\x00\xd3\xa7\xabA'
self.assertEqual(parse_bucket(data), ['sulfur_dio', 27, 21.456945419311523])
def test_parse_bin(self):
data = b'\x82\x00\x00\x00\x03\x00\x00\x00ice\x06\x00\x00\x00ethene\x07\x00\x00\x00methane\x0b\x00\x00\x00carbon_mono\n\x00\x00\x00carbon_dio\x07\x00\x00\x00ammonia\x0c\x00\x00\x00hydrogen_sul\n\x00\x00\x00sulfur_dio\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00'
self.assertEqual(parse_topic('srcp2_msgs/HaulerMsg', data), [['ice', 'ethene', 'methane', 'carbon_mono', 'carbon_dio', 'ammonia', 'hydrogen_sul', 'sulfur_dio'], [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]])
def test_parse_score_qual2(self):
data = b'\x87\x00\x00\x00\x03\x00\x00\x00ice\x06\x00\x00\x00ethene\x07\x00\x00\x00methane' + \
b'\x08\x00\x00\x00carbon_mono\n\x00\x00\x00carbon_dio\x07\x00\x00\x00ammonia\x0c\x00\x00\x00' + \
b'hydrogen_sul\n\x00\x00\x00sulfur_dio\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' + \
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' + \
b'\x00\x00\x00\x00\x00\x00\x00\x00\x00'
self.assertEqual(parse_topic('srcp2_msgs/Qual2ScoringMsg', data), [0, 0])
def test_radio(self):
data = b'radio X30F60R [0, 100, 30]\n'
bus = MagicMock()
r = ROSMsgParser(config={}, bus=bus)
r.slot_raw(timestamp=None, data=data)
bus.publish.assert_called_with('radio', [b'X30F60R', b'[0, 100, 30]\n'])
def test_publish_desired_speed(self):
data = b'\x08\x00\x00\x00\x02\x00\x00\x00\x00\x06\x81\x14' # clock as 8 bytes
bus = MagicMock()
r = ROSMsgParser(config={}, bus=bus)
r.slot_raw(timestamp=None, data=data)
bus.publish.assert_called_with('sim_time_sec', 2)
clock_data = b'\x08\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00' # clock 3s
r.slot_raw(timestamp=None, data=clock_data)
bus.publish.assert_called_with('sim_time_sec', 3) # initially desired speed is None -> no cmd
r.slot_desired_speed(timestamp=None, data=[0, 0])
r.slot_raw(timestamp=None, data=clock_data)
# ... asserting that the last call has been made in a particular way
bus.publish.assert_called_with('cmd', b'cmd_vel 0.000000 0.000000')
# after update from 3D desired speed only extended cmd_vel_3d should be used
r.slot_desired_speed_3d(timestamp=None, data=[[1, 2, 3], [4, 5, 6]])
r.slot_raw(timestamp=None, data=clock_data)
bus.publish.assert_called_with('cmd', b'cmd_vel_3d 1.000000 2.000000 3.000000 4.000000 5.000000 6.000000')
def test_publish_undefined_desired_speed(self):
# for the drone it is important not to send any command until the very first desired speed is received
pass
# vim: expandtab sw=4 ts=4 | en | 0.95475 | # clock as 8 bytes # clock 3s # initially desired speed is None -> no cmd # ... asserting that the last call has been made in a particular way # after update from 3D desired speed only extended cmd_vel_3d should be used # for the drone it is important not to send any command until the very first desired speed is received # vim: expandtab sw=4 ts=4 | 2.567743 | 3 |
src/PyEvalJS/runtime.py | Satireven/PyEvalJS | 0 | 6620579 | <reponame>Satireven/PyEvalJS<filename>src/PyEvalJS/runtime.py
import sys
import json
from ctypes import *
from .error import JSError
from .utils import get_lib_path
class Runtime:
def __init__(self):
self.chakraCore = CDLL(get_lib_path())
self._mcode = ["""var replace = function(k,v) {
if (typeof v === 'function') {
return Function.prototype.toString.call(v)
} else if (v === undefined ) {
return null
} else {
return v
} };"""]
self._count = 0
self._init_runtime()
self._init_context()
# call DllMain manually on non-Windows
if sys.platform != "win32":
# Attach process
self.chakraCore.DllMain(0, 1, 0)
# Attach main thread
self.chakraCore.DllMain(0, 2, 0)
def _init_runtime(self):
self.runtime = c_void_p()
self.chakraCore.JsCreateRuntime(0, 0, byref(self.runtime))
def _init_context(self):
self.context = c_void_p()
self.chakraCore.JsCreateContext(self.runtime, byref(self.context))
self.chakraCore.JsSetCurrentContext(self.context)
def __del__(self):
# Dispose runtime
self.chakraCore.JsDisposeRuntime(self.runtime)
def _get_exception(self):
exception = c_void_p()
self.chakraCore.JsGetAndClearException(byref(exception))
exception_id = c_void_p()
self.chakraCore.JsCreatePropertyId(b"message", 7, byref(exception_id))
value = c_void_p()
self.chakraCore.JsGetProperty(exception, exception_id, byref(value))
return self._js_value_to_str(value)
def _js_value_to_str(self,jsResult):
# Convert script result to String in JavaScript; redundant if script returns a String
resultJSString = c_void_p()
self.chakraCore.JsConvertValueToString(jsResult, byref(resultJSString))
stringLength = c_size_t()
# Get buffer size needed for the result string
self.chakraCore.JsCopyString(resultJSString, 0, 0, byref(stringLength))
resultSTR = create_string_buffer(stringLength.value + 1); # buffer is big enough to store the result
# Get String from JsValueRef
self.chakraCore.JsCopyString(resultJSString, byref(resultSTR), stringLength.value + 1, 0)
# Set `null-ending` to the end
resultSTRLastByte = (c_char * stringLength.value).from_address(addressof(resultSTR))
resultSTRLastByte = '\0'
return resultSTR.value.decode('utf8')
def eval(self,script):
self._count += 1
if self._count == 5: # Reset Context Incase exploied
self._init_context()
self._count = 0
script = '\n'.join(self._mcode)+'''\nJSON.stringify(eval(%s),replace);'''%repr(script)
script = create_string_buffer(script.encode('UTF-16'))
fname = c_void_p()
# create JsValueRef from filename
self.chakraCore.JsCreateString("", 0, byref(fname))
scriptSource = c_void_p()
# Create ArrayBuffer from script source
self.chakraCore.JsCreateExternalArrayBuffer(script, len(script), 0, 0, byref(scriptSource))
jsResult = c_void_p()
# Run the script.
err = self.chakraCore.JsRun(scriptSource, 0 , fname, 0x02, byref(jsResult))
if err == 0:
return json.loads(self._js_value_to_str(jsResult))
# js exception
elif err == 196609:
raise JSError(self._get_exception())
# other error
else:
raise Exception(jsResult)
def set_variable(self,name,value):
self.eval("var %s = %s" % (name, json.dumps(value)))
return True
def get_variable(self,name):
value = self.eval("JSON.stringify((() => %s)())" % name)
return json.loads(value)
def require(self,js_file):
with open(js_file,'r',encoding='utf-8',errors='ignore') as f:
self._mcode.append(f.read())
def compile(self,script):
'''Add some function to the context. But not Running, wait for Call.If you want to run it,just eval it.'''
self._mcode.append(script)
def call(self,identifier,*args):
args = json.dumps(args)
return self.eval("%s.apply(this, %s)"%(identifier, args))
def call_for_each(self,identifier,*args):
'''Call the same function for each item in the list'''
args = json.dumps(args)
script = '''function callForEverybody(bodys) { return bodys.map(x => %s(x));}
callForEverybody.apply(this,%s);'''%(identifier,args)
return self.eval(script) | import sys
import json
from ctypes import *
from .error import JSError
from .utils import get_lib_path
class Runtime:
def __init__(self):
self.chakraCore = CDLL(get_lib_path())
self._mcode = ["""var replace = function(k,v) {
if (typeof v === 'function') {
return Function.prototype.toString.call(v)
} else if (v === undefined ) {
return null
} else {
return v
} };"""]
self._count = 0
self._init_runtime()
self._init_context()
# call DllMain manually on non-Windows
if sys.platform != "win32":
# Attach process
self.chakraCore.DllMain(0, 1, 0)
# Attach main thread
self.chakraCore.DllMain(0, 2, 0)
def _init_runtime(self):
self.runtime = c_void_p()
self.chakraCore.JsCreateRuntime(0, 0, byref(self.runtime))
def _init_context(self):
self.context = c_void_p()
self.chakraCore.JsCreateContext(self.runtime, byref(self.context))
self.chakraCore.JsSetCurrentContext(self.context)
def __del__(self):
# Dispose runtime
self.chakraCore.JsDisposeRuntime(self.runtime)
def _get_exception(self):
exception = c_void_p()
self.chakraCore.JsGetAndClearException(byref(exception))
exception_id = c_void_p()
self.chakraCore.JsCreatePropertyId(b"message", 7, byref(exception_id))
value = c_void_p()
self.chakraCore.JsGetProperty(exception, exception_id, byref(value))
return self._js_value_to_str(value)
def _js_value_to_str(self,jsResult):
# Convert script result to String in JavaScript; redundant if script returns a String
resultJSString = c_void_p()
self.chakraCore.JsConvertValueToString(jsResult, byref(resultJSString))
stringLength = c_size_t()
# Get buffer size needed for the result string
self.chakraCore.JsCopyString(resultJSString, 0, 0, byref(stringLength))
resultSTR = create_string_buffer(stringLength.value + 1); # buffer is big enough to store the result
# Get String from JsValueRef
self.chakraCore.JsCopyString(resultJSString, byref(resultSTR), stringLength.value + 1, 0)
# Set `null-ending` to the end
resultSTRLastByte = (c_char * stringLength.value).from_address(addressof(resultSTR))
resultSTRLastByte = '\0'
return resultSTR.value.decode('utf8')
def eval(self,script):
self._count += 1
if self._count == 5: # Reset Context Incase exploied
self._init_context()
self._count = 0
script = '\n'.join(self._mcode)+'''\nJSON.stringify(eval(%s),replace);'''%repr(script)
script = create_string_buffer(script.encode('UTF-16'))
fname = c_void_p()
# create JsValueRef from filename
self.chakraCore.JsCreateString("", 0, byref(fname))
scriptSource = c_void_p()
# Create ArrayBuffer from script source
self.chakraCore.JsCreateExternalArrayBuffer(script, len(script), 0, 0, byref(scriptSource))
jsResult = c_void_p()
# Run the script.
err = self.chakraCore.JsRun(scriptSource, 0 , fname, 0x02, byref(jsResult))
if err == 0:
return json.loads(self._js_value_to_str(jsResult))
# js exception
elif err == 196609:
raise JSError(self._get_exception())
# other error
else:
raise Exception(jsResult)
def set_variable(self,name,value):
self.eval("var %s = %s" % (name, json.dumps(value)))
return True
def get_variable(self,name):
value = self.eval("JSON.stringify((() => %s)())" % name)
return json.loads(value)
def require(self,js_file):
with open(js_file,'r',encoding='utf-8',errors='ignore') as f:
self._mcode.append(f.read())
def compile(self,script):
'''Add some function to the context. But not Running, wait for Call.If you want to run it,just eval it.'''
self._mcode.append(script)
def call(self,identifier,*args):
args = json.dumps(args)
return self.eval("%s.apply(this, %s)"%(identifier, args))
def call_for_each(self,identifier,*args):
'''Call the same function for each item in the list'''
args = json.dumps(args)
script = '''function callForEverybody(bodys) { return bodys.map(x => %s(x));}
callForEverybody.apply(this,%s);'''%(identifier,args)
return self.eval(script) | en | 0.433278 | var replace = function(k,v) { if (typeof v === 'function') { return Function.prototype.toString.call(v) } else if (v === undefined ) { return null } else { return v } }; # call DllMain manually on non-Windows # Attach process # Attach main thread # Dispose runtime # Convert script result to String in JavaScript; redundant if script returns a String # Get buffer size needed for the result string # buffer is big enough to store the result # Get String from JsValueRef # Set `null-ending` to the end # Reset Context Incase exploied \nJSON.stringify(eval(%s),replace); # create JsValueRef from filename # Create ArrayBuffer from script source # Run the script. # js exception # other error Add some function to the context. But not Running, wait for Call.If you want to run it,just eval it. Call the same function for each item in the list function callForEverybody(bodys) { return bodys.map(x => %s(x));} callForEverybody.apply(this,%s); | 1.945695 | 2 |
tests/test_qa4sm_named_attrs.py | wpreimes/qa4sm-reader | 0 | 6620580 | <reponame>wpreimes/qa4sm-reader
# -*- coding: utf-8 -*-
from qa4sm_reader.handlers import QA4SMNamedAttributes
from tests.test_qa4sm_attrs import test_attributes
import unittest
class TestQA4SMNamedAttributes(unittest.TestCase):
def setUp(self) -> None:
attrs = test_attributes()
self.ismn = QA4SMNamedAttributes(id=6, short_name='ISMN', global_attrs=attrs)
self.c3s17 = QA4SMNamedAttributes(id=1, short_name='C3S', global_attrs=attrs)
self.c3s18 = QA4SMNamedAttributes(id=2, short_name='C3S', global_attrs=attrs)
self.smos = QA4SMNamedAttributes(id=3, short_name='SMOS', global_attrs=attrs)
self.smap = QA4SMNamedAttributes(id=4, short_name='SMAP', global_attrs=attrs)
self.ascat = QA4SMNamedAttributes(id=5, short_name='ASCAT', global_attrs=attrs)
def test_eq(self):
assert self.ismn != self.ascat
assert self.ismn == self.ismn
assert self.ascat == self.ascat
def test_names(self):
assert self.ismn.pretty_name() == 'ISMN'
assert self.ismn.pretty_version() == '20180712 mini testset'
assert self.c3s17.pretty_name() == 'C3S'
assert self.c3s17.pretty_version() == 'v201706'
assert self.c3s18.pretty_name() == 'C3S'
assert self.c3s18.pretty_version() == 'v201812'
assert self.smos.pretty_name() == 'SMOS IC'
assert self.smos.pretty_version() == 'V.105 Ascending'
assert self.smap.pretty_name() == 'SMAP level 3'
assert self.smap.pretty_version() == 'v5 PM/ascending'
assert self.ascat.pretty_name() == 'H-SAF ASCAT SSM CDR'
assert self.ascat.pretty_version() == 'H113'
if __name__ == '__main__':
suite = unittest.TestSuite()
suite.addTest(TestQA4SMNamedAttributes("test_eq"))
runner = unittest.TextTestRunner()
runner.run(suite)
| # -*- coding: utf-8 -*-
from qa4sm_reader.handlers import QA4SMNamedAttributes
from tests.test_qa4sm_attrs import test_attributes
import unittest
class TestQA4SMNamedAttributes(unittest.TestCase):
def setUp(self) -> None:
attrs = test_attributes()
self.ismn = QA4SMNamedAttributes(id=6, short_name='ISMN', global_attrs=attrs)
self.c3s17 = QA4SMNamedAttributes(id=1, short_name='C3S', global_attrs=attrs)
self.c3s18 = QA4SMNamedAttributes(id=2, short_name='C3S', global_attrs=attrs)
self.smos = QA4SMNamedAttributes(id=3, short_name='SMOS', global_attrs=attrs)
self.smap = QA4SMNamedAttributes(id=4, short_name='SMAP', global_attrs=attrs)
self.ascat = QA4SMNamedAttributes(id=5, short_name='ASCAT', global_attrs=attrs)
def test_eq(self):
assert self.ismn != self.ascat
assert self.ismn == self.ismn
assert self.ascat == self.ascat
def test_names(self):
assert self.ismn.pretty_name() == 'ISMN'
assert self.ismn.pretty_version() == '20180712 mini testset'
assert self.c3s17.pretty_name() == 'C3S'
assert self.c3s17.pretty_version() == 'v201706'
assert self.c3s18.pretty_name() == 'C3S'
assert self.c3s18.pretty_version() == 'v201812'
assert self.smos.pretty_name() == 'SMOS IC'
assert self.smos.pretty_version() == 'V.105 Ascending'
assert self.smap.pretty_name() == 'SMAP level 3'
assert self.smap.pretty_version() == 'v5 PM/ascending'
assert self.ascat.pretty_name() == 'H-SAF ASCAT SSM CDR'
assert self.ascat.pretty_version() == 'H113'
if __name__ == '__main__':
suite = unittest.TestSuite()
suite.addTest(TestQA4SMNamedAttributes("test_eq"))
runner = unittest.TextTestRunner()
runner.run(suite) | en | 0.769321 | # -*- coding: utf-8 -*- | 2.205387 | 2 |
memegen/meme_template.py | WalterSimoncini/memegen-api | 0 | 6620581 | from enum import Enum
class MemeTemplate(str, Enum):
DRAKE = "drake"
| from enum import Enum
class MemeTemplate(str, Enum):
DRAKE = "drake"
| none | 1 | 2.536753 | 3 | |
helper_code/concatenate_videos.py | BrancoLab/escape-analysis | 0 | 6620582 | <gh_stars>0
'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
-----------# Display a saved video --------------------------------
'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
import cv2
import numpy as np
import glob
# ------------------------------------------
# Select video file name and folder location
# ------------------------------------------
save_folder = 'D:\\data\\Summary Plots\\videos\\'
''' SV1 - visualization '''
# file_loc = 'D:\\data\\Paper\\Circle wall down dark\\'
# mouse_names = ['CA4030']
# save_name = 'SV1 real.mp4'
''' SV2 - homing vector '''
# file_loc = 'D:\\data\\Paper\\Circle wall up\\'
# mouse_names = ['CA3482', 'CA7190', 'CA7170'] #, 'CA3210'] # 'CA3471', 'CA3483',
# save_name = 'SV1.mp4'
''' SV3 - obstacle '''
# file_loc1 = 'D:\\data\\Paper\\Circle wall down\\'
# file_loc2 = 'D:\\data\\Paper\\Circle lights on off (baseline)\\'
# # file_locs = [file_loc1, file_loc2, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2, file_loc2]
# # mouse_names = ['CA6940', 'CA7503', 'CA8110', 'CA8140', 'CA3400', 'CA3151', 'CA7491', 'CA8190']
# file_locs = [file_loc1, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2] # file_loc2, file_loc2,
# mouse_names = ['CA6940', 'CA7503','CA8110', 'CA3400', 'CA3380'] # 'CA7491', 'CA8140', 'CA8190',
# save_name = 'SV_trial1.mp4'
#
# file_locs = [file_loc1, file_loc1, file_loc1] # file_loc2, file_loc2,
# mouse_names = ['CA3400', 'CA3410','CA3380'] # 'CA7491', 'CA8140', 'CA8190',
# save_name = 'SV_trial3.mp4'
''' SV4 - wall up '''
# file_loc = 'D:\\data\\Paper\\Circle wall up\\'
# mouse_names = ['CA3210', 'CA3471', 'CA7170','CA7190']
# save_name = 'SV4.mp4'
''' SV5 - dark '''
# file_loc = 'D:\\data\\Paper\\Circle wall down dark\\'
# mouse_names = ['CA8180','CA8792','CA8462','CA8794']
# save_name = 'SV5.mp4'
# file_loc = 'D:\\data\\Paper\\Circle wall down (dark non naive)\\'
# mouse_names = ['CA3720','CA8541','CA3740','CA8551']
# save_name = 'SV5II.mp4'
''' SV6 - wall down '''
# file_loc = 'D:\\data\\Paper\\Circle wall down\\'
# mouse_names = ['CA3380', 'CA3410', 'CA3400','CA6950', 'CA3390', 'CA3151']
# save_name = 'SV6.mp4'
file_loc1 = 'D:\\data\\Paper\\Circle wall down\\'
file_loc2 = 'D:\\data\\Paper\\Circle wall down (no baseline)\\'
mouse_names = ['CA3151', 'CA3410', 'CA3410', 'CA6970','CA3390','CA3390']
file_locs = [file_loc1, file_loc1, file_loc1, file_loc2, file_loc1, file_loc1]
save_name = 'SV6 II.mp4'
''' SV7 - wall left '''
# file_loc = 'D:\\data\\Paper\\Square wall moves left\\'
# mouse_names = ['CA6950', 'CA8180', 'CA8180', 'CA7501', 'CA6990', 'CA7220']
# save_name = 'SV7.mp4'
''' SV8 - food '''
# file_loc = 'D:\\data\\Paper\\Circle food wall down\\'
# mouse_names = ['CA8380','CA8380', 'CA8390', 'CA8360']
# save_name = 'SV8.mp4'
# mouse_names = ['CA8380', 'CA8370', 'CA8360', 'CA8360']
# save_name = 'SV8 II.mp4'
save_fps = 30
color = True
# more options
show_video = True
display_frame_rate = 1000
# set up video writer
fourcc_data = cv2.VideoWriter_fourcc(*"XVID") # LJPG for lossless, XVID for compressed
data_video = cv2.VideoWriter(save_folder + save_name, fourcc_data, save_fps, (720, 720), color)
# loop across all videos
for m, mouse in enumerate(mouse_names):
# vids to concatenate
# vid_paths = glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[:2] # 2
# vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[0]] # 3
# vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[2]] # 3 II
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 4
# if not mouse == 'CA8792' and not mouse == 'CA8180': vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 5 I
# else: vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[1]] # 5 I
# if m==0: i = 2
# elif m == 1: i = 4
# elif m == 2: i = 3
# elif m == 3: i = 1
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 5 II
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 6
if m==0: i = 4
elif m == 1: i = 6
elif m == 2: i = 7
elif m == 3: i = 1
elif m == 4: i = 5
elif m == 5: i = 6
vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[i]] # 6 II
# if m==0: i = 1
# elif m == 1: i = 2
# elif m == 2: i = 3
# elif m == 3: i = 3
# elif m == 4: i = 2
# elif m == 5: i = 2
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 7
# if m==0: i = 6
# elif m == 1: i = 10
# elif m == 2: i = 6
# elif m == 3: i = 7
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8
# if m==0: i = 18
# elif m == 1: i = 17
# elif m == 2: i = 15
# elif m == 3: i = 19
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8 II
for vid_path in vid_paths:
# ---------------------------
# Play video and save video
# ---------------------------
vid = cv2.VideoCapture(vid_path)
while True:
ret, frame = vid.read() # read the frame
frame_num = vid.get(cv2.CAP_PROP_POS_FRAMES)
if ret:
# write the new video
data_video.write(frame)
# display the video
if show_video:
cv2.imshow('movie', frame)
if cv2.waitKey(int(1000 / display_frame_rate)) & 0xFF == ord('q'): break
# if can't read the video
else:
break
# close the video files
vid.release()
data_video.release()
print('done')
| '''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
-----------# Display a saved video --------------------------------
'''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
import cv2
import numpy as np
import glob
# ------------------------------------------
# Select video file name and folder location
# ------------------------------------------
save_folder = 'D:\\data\\Summary Plots\\videos\\'
''' SV1 - visualization '''
# file_loc = 'D:\\data\\Paper\\Circle wall down dark\\'
# mouse_names = ['CA4030']
# save_name = 'SV1 real.mp4'
''' SV2 - homing vector '''
# file_loc = 'D:\\data\\Paper\\Circle wall up\\'
# mouse_names = ['CA3482', 'CA7190', 'CA7170'] #, 'CA3210'] # 'CA3471', 'CA3483',
# save_name = 'SV1.mp4'
''' SV3 - obstacle '''
# file_loc1 = 'D:\\data\\Paper\\Circle wall down\\'
# file_loc2 = 'D:\\data\\Paper\\Circle lights on off (baseline)\\'
# # file_locs = [file_loc1, file_loc2, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2, file_loc2]
# # mouse_names = ['CA6940', 'CA7503', 'CA8110', 'CA8140', 'CA3400', 'CA3151', 'CA7491', 'CA8190']
# file_locs = [file_loc1, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2] # file_loc2, file_loc2,
# mouse_names = ['CA6940', 'CA7503','CA8110', 'CA3400', 'CA3380'] # 'CA7491', 'CA8140', 'CA8190',
# save_name = 'SV_trial1.mp4'
#
# file_locs = [file_loc1, file_loc1, file_loc1] # file_loc2, file_loc2,
# mouse_names = ['CA3400', 'CA3410','CA3380'] # 'CA7491', 'CA8140', 'CA8190',
# save_name = 'SV_trial3.mp4'
''' SV4 - wall up '''
# file_loc = 'D:\\data\\Paper\\Circle wall up\\'
# mouse_names = ['CA3210', 'CA3471', 'CA7170','CA7190']
# save_name = 'SV4.mp4'
''' SV5 - dark '''
# file_loc = 'D:\\data\\Paper\\Circle wall down dark\\'
# mouse_names = ['CA8180','CA8792','CA8462','CA8794']
# save_name = 'SV5.mp4'
# file_loc = 'D:\\data\\Paper\\Circle wall down (dark non naive)\\'
# mouse_names = ['CA3720','CA8541','CA3740','CA8551']
# save_name = 'SV5II.mp4'
''' SV6 - wall down '''
# file_loc = 'D:\\data\\Paper\\Circle wall down\\'
# mouse_names = ['CA3380', 'CA3410', 'CA3400','CA6950', 'CA3390', 'CA3151']
# save_name = 'SV6.mp4'
file_loc1 = 'D:\\data\\Paper\\Circle wall down\\'
file_loc2 = 'D:\\data\\Paper\\Circle wall down (no baseline)\\'
mouse_names = ['CA3151', 'CA3410', 'CA3410', 'CA6970','CA3390','CA3390']
file_locs = [file_loc1, file_loc1, file_loc1, file_loc2, file_loc1, file_loc1]
save_name = 'SV6 II.mp4'
''' SV7 - wall left '''
# file_loc = 'D:\\data\\Paper\\Square wall moves left\\'
# mouse_names = ['CA6950', 'CA8180', 'CA8180', 'CA7501', 'CA6990', 'CA7220']
# save_name = 'SV7.mp4'
''' SV8 - food '''
# file_loc = 'D:\\data\\Paper\\Circle food wall down\\'
# mouse_names = ['CA8380','CA8380', 'CA8390', 'CA8360']
# save_name = 'SV8.mp4'
# mouse_names = ['CA8380', 'CA8370', 'CA8360', 'CA8360']
# save_name = 'SV8 II.mp4'
save_fps = 30
color = True
# more options
show_video = True
display_frame_rate = 1000
# set up video writer
fourcc_data = cv2.VideoWriter_fourcc(*"XVID") # LJPG for lossless, XVID for compressed
data_video = cv2.VideoWriter(save_folder + save_name, fourcc_data, save_fps, (720, 720), color)
# loop across all videos
for m, mouse in enumerate(mouse_names):
# vids to concatenate
# vid_paths = glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[:2] # 2
# vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[0]] # 3
# vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[2]] # 3 II
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 4
# if not mouse == 'CA8792' and not mouse == 'CA8180': vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 5 I
# else: vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[1]] # 5 I
# if m==0: i = 2
# elif m == 1: i = 4
# elif m == 2: i = 3
# elif m == 3: i = 1
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 5 II
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 6
if m==0: i = 4
elif m == 1: i = 6
elif m == 2: i = 7
elif m == 3: i = 1
elif m == 4: i = 5
elif m == 5: i = 6
vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[i]] # 6 II
# if m==0: i = 1
# elif m == 1: i = 2
# elif m == 2: i = 3
# elif m == 3: i = 3
# elif m == 4: i = 2
# elif m == 5: i = 2
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 7
# if m==0: i = 6
# elif m == 1: i = 10
# elif m == 2: i = 6
# elif m == 3: i = 7
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8
# if m==0: i = 18
# elif m == 1: i = 17
# elif m == 2: i = 15
# elif m == 3: i = 19
# vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8 II
for vid_path in vid_paths:
# ---------------------------
# Play video and save video
# ---------------------------
vid = cv2.VideoCapture(vid_path)
while True:
ret, frame = vid.read() # read the frame
frame_num = vid.get(cv2.CAP_PROP_POS_FRAMES)
if ret:
# write the new video
data_video.write(frame)
# display the video
if show_video:
cv2.imshow('movie', frame)
if cv2.waitKey(int(1000 / display_frame_rate)) & 0xFF == ord('q'): break
# if can't read the video
else:
break
# close the video files
vid.release()
data_video.release()
print('done') | en | 0.552523 | -----------# Display a saved video -------------------------------- # ------------------------------------------ # Select video file name and folder location # ------------------------------------------ SV1 - visualization # file_loc = 'D:\\data\\Paper\\Circle wall down dark\\' # mouse_names = ['CA4030'] # save_name = 'SV1 real.mp4' SV2 - homing vector # file_loc = 'D:\\data\\Paper\\Circle wall up\\' # mouse_names = ['CA3482', 'CA7190', 'CA7170'] #, 'CA3210'] # 'CA3471', 'CA3483', # save_name = 'SV1.mp4' SV3 - obstacle # file_loc1 = 'D:\\data\\Paper\\Circle wall down\\' # file_loc2 = 'D:\\data\\Paper\\Circle lights on off (baseline)\\' # # file_locs = [file_loc1, file_loc2, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2, file_loc2] # # mouse_names = ['CA6940', 'CA7503', 'CA8110', 'CA8140', 'CA3400', 'CA3151', 'CA7491', 'CA8190'] # file_locs = [file_loc1, file_loc2, file_loc2, file_loc1, file_loc1, file_loc2] # file_loc2, file_loc2, # mouse_names = ['CA6940', 'CA7503','CA8110', 'CA3400', 'CA3380'] # 'CA7491', 'CA8140', 'CA8190', # save_name = 'SV_trial1.mp4' # # file_locs = [file_loc1, file_loc1, file_loc1] # file_loc2, file_loc2, # mouse_names = ['CA3400', 'CA3410','CA3380'] # 'CA7491', 'CA8140', 'CA8190', # save_name = 'SV_trial3.mp4' SV4 - wall up # file_loc = 'D:\\data\\Paper\\Circle wall up\\' # mouse_names = ['CA3210', 'CA3471', 'CA7170','CA7190'] # save_name = 'SV4.mp4' SV5 - dark # file_loc = 'D:\\data\\Paper\\Circle wall down dark\\' # mouse_names = ['CA8180','CA8792','CA8462','CA8794'] # save_name = 'SV5.mp4' # file_loc = 'D:\\data\\Paper\\Circle wall down (dark non naive)\\' # mouse_names = ['CA3720','CA8541','CA3740','CA8551'] # save_name = 'SV5II.mp4' SV6 - wall down # file_loc = 'D:\\data\\Paper\\Circle wall down\\' # mouse_names = ['CA3380', 'CA3410', 'CA3400','CA6950', 'CA3390', 'CA3151'] # save_name = 'SV6.mp4' SV7 - wall left # file_loc = 'D:\\data\\Paper\\Square wall moves left\\' # mouse_names = ['CA6950', 'CA8180', 'CA8180', 'CA7501', 'CA6990', 'CA7220'] # save_name = 'SV7.mp4' SV8 - food # file_loc = 'D:\\data\\Paper\\Circle food wall down\\' # mouse_names = ['CA8380','CA8380', 'CA8390', 'CA8360'] # save_name = 'SV8.mp4' # mouse_names = ['CA8380', 'CA8370', 'CA8360', 'CA8360'] # save_name = 'SV8 II.mp4' # more options # set up video writer # LJPG for lossless, XVID for compressed # loop across all videos # vids to concatenate # vid_paths = glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[:2] # 2 # vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[0]] # 3 # vid_paths = [glob.glob(file_locs[m] + mouse + '\\' + '*vid (DLC)*')[2]] # 3 II # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 4 # if not mouse == 'CA8792' and not mouse == 'CA8180': vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 5 I # else: vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[1]] # 5 I # if m==0: i = 2 # elif m == 1: i = 4 # elif m == 2: i = 3 # elif m == 3: i = 1 # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 5 II # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[3]] # 6 # 6 II # if m==0: i = 1 # elif m == 1: i = 2 # elif m == 2: i = 3 # elif m == 3: i = 3 # elif m == 4: i = 2 # elif m == 5: i = 2 # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 7 # if m==0: i = 6 # elif m == 1: i = 10 # elif m == 2: i = 6 # elif m == 3: i = 7 # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8 # if m==0: i = 18 # elif m == 1: i = 17 # elif m == 2: i = 15 # elif m == 3: i = 19 # vid_paths = [glob.glob(file_loc + mouse + '\\' + '*vid (DLC)*')[i]] # 8 II # --------------------------- # Play video and save video # --------------------------- # read the frame # write the new video # display the video # if can't read the video # close the video files | 1.969091 | 2 |
reprod.py | YBRua/DataMiningProject | 0 | 6620583 | <reponame>YBRua/DataMiningProject
import copy
import pickle
import random
import itertools
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy
from typing import Dict, List
from torch.utils.data import DataLoader, IterableDataset
from freq_counter import FreqCounter
from argparse import ArgumentParser
from baseline.metric import batch_ndcg_torch, batched_average_precision, batched_hit_ratio, batched_reciprocal_rank
import data_io
from common import *
from metrics import MAP, NDCG, HR, RR, Loss
def parse_args():
parser = ArgumentParser()
parser.add_argument(
'--epoch', '-e', type=int, default=20,
help='Number of training epoches')
parser.add_argument(
'--batchsize', '-b', type=int, default=64,
help='Batch size')
parser.add_argument(
'--dataset', '-d', choices=['bookcross', 'music'],
default='bookcross',
help='Dataset, can be one of bobookcrossok or music')
parser.add_argument(
'--device', type=str, default='cuda:0',
help='PyTorch style device to run the model')
return parser.parse_args()
def prepare_dataset(dataset: str):
assert dataset in ['bookcross', 'music'], f'Invalid dataset: {dataset}'
train_raw = data_io.load_rating_file_as_matrix(f'data/{dataset}.train.rating')
train_smp = data_io.load_train_entries(f'data/{dataset}.train.rating')
test = data_io.load_test_entries(f'data/{dataset}', False)
if dataset == 'bookcross':
feature_dict_path = 'data/book_info_bookcross'
user_feat_path = 'data/user_hist_withinfo_bookcross'
else:
feature_dict_path = 'data/song_info_music_HK'
user_feat_path = 'data/user_hist_withinfo_music_HK'
features_dict = pickle.load(open(feature_dict_path, 'rb'))
user_features_dict = pickle.load(open(user_feat_path, 'rb'))
return train_raw, train_smp, test, features_dict, user_features_dict
class SelfAttention(nn.Module):
def __init__(self, nhead, i, kq, v):
super().__init__()
self.attn_k = nn.Linear(i, kq, bias=False)
self.attn_q = nn.Linear(i, kq, bias=False)
self.attn_v = nn.Linear(i, v, bias=False)
self.nhead = nhead
def forward(self, x):
# x: ...ni
k = self.attn_k(x).reshape(*x.shape[:-1], self.nhead, -1)
q = self.attn_q(x).reshape(*x.shape[:-1], self.nhead, -1)
v = self.attn_v(x).reshape(*x.shape[:-1], self.nhead, -1)
attn = torch.softmax(
torch.einsum("...nhd,...mhd->...nmh", k, q) / k.shape[-1] ** 0.5,
-2
)
return torch.einsum("...nmh,...mhd->...nhd", attn, v).flatten(-2)
class SAF(nn.Module):
def __init__(self):
super().__init__()
self.user_embed = nn.Embedding(90000, 300)
self.item_embed = nn.Embedding(90000, 300)
with torch.no_grad():
self.user_embed.weight.uniform_(-0.05, 0.05)
self.item_embed.weight.uniform_(-0.05, 0.05)
self.attn = SelfAttention(5, 300, 600, 600)
self.drop = nn.Dropout(0.4)
self.proj = nn.Linear(600, 300)
self.linear = nn.Linear(300, 1)
self.norm = nn.LayerNorm(300)
def encode(self, user_features, item_features):
# bNMd
item = self.item_embed(item_features)
# bL4d
user = self.user_embed(user_features).mean(2) # bLd
user = user.unsqueeze(1).repeat(1, item.shape[1], 1, 1) # bNLd
sa_pre = torch.cat([user, item], 2) # bN (L+M) d
sa_post = self.norm(self.proj(self.attn(sa_pre)) + sa_pre).mean(-2) # bNd
return sa_post
def forward(self, user_ids, item_ids, user_features, item_features, labels=None):
sa_post = self.encode(user_features, item_features)
return self.linear(self.drop(sa_post)).squeeze()
class RankingAwareNet(nn.Module):
def __init__(self, encoder: SAF):
super().__init__()
self.encoder = encoder
self.impf = nn.Sequential(
nn.Linear(300, 1024),
nn.LayerNorm(1024), nn.ReLU(),
)
self.cls = nn.Sequential(
nn.Dropout(), nn.Linear(1324, 1)
)
def forward(self, user_ids, item_ids, user_features, item_features, labels=None):
with torch.no_grad():
sa_post = self.encoder.encode(user_features, item_features)
impf = self.impf(sa_post).max(-2)[0].unsqueeze(-2).repeat(1, sa_post.shape[1], 1)
pf = torch.cat([impf, sa_post], dim=-1)
return self.cls(pf).squeeze()
def get_train_instances(train, ufd, ifd):
user_input, item_input, labels = [], [], []
user_ids = []
item_ids = []
for (u, i) in train.keys():
user_ids.append(u)
item_ids.append(i)
user_input.append(numpy.array(ufd[u]).reshape(-1, 4))
item_input.append(numpy.array(ifd[i][:4])[None])
if train[(u, i)] == 1:
labels.append(1)
if train[(u, i)] == -1:
labels.append(0)
return [*zip(user_ids, item_ids, user_input, item_input, labels)]
class Rekommand(IterableDataset):
def __init__(
self, entries: List[data_io.TestEntry],
item_feature_dict: Dict[int, List[int]],
user_feature_dict: Dict[int, List[int]],
pos_per_entry: int = 5, neg_per_entry: int = 50,
background_neg_samples: int = 0,
full: bool = False
) -> None:
super().__init__()
self.full = full
self.ppe = pos_per_entry
self.npe = neg_per_entry
self.bns = background_neg_samples
self.entries = entries
self.ifd = item_feature_dict
self.ufd = user_feature_dict
self.valid_items = list(self.ifd.keys())
self.cum_weights = [*itertools.accumulate(map(
lambda x: len(x.positives) + len(x.negatives), self.entries
))]
def __iter__(self):
rng = len(self.entries) if self.full else 2 ** 30
for i in range(rng):
entry = self.entries[i] if self.full else\
random.choices(self.entries, cum_weights=self.cum_weights, k=1)[0]
entry = copy.deepcopy(entry)
if not self.full:
if not len(entry.positives):
continue
entry.positives = random.choices(entry.positives, k=self.ppe)
# entry.negatives = random.choices(entry.negatives, k=self.npe)
entry.negatives = random.choices(self.valid_items, k=self.npe)
items = numpy.array(list(entry.positives) + list(entry.negatives))
item_features = numpy.array([self.ifd[x][:4] for x in items])
user_features = numpy.array(self.ufd[entry.id]).reshape(-1, 4)
labels = numpy.concatenate([
numpy.ones_like(entry.positives),
numpy.zeros_like(entry.negatives)
])
randperm = numpy.random.permutation(len(items))
yield entry.id, items[randperm], user_features, item_features[randperm], labels[randperm]
def __length_hint__(self):
return len(self.entries) if self.full else 2 * len(self.entries)
def main():
args = parse_args()
DEVICE = torch.device(args.device)
BATCH_SIZE = args.batchsize
EPOCHES = args.epoch
train_raw, train_smp, test, features_dict, user_features_dict = prepare_dataset(args.dataset)
target = FreqCounter(train_smp)
train_smp = Rekommand(train_smp, features_dict, user_features_dict)
test = Rekommand(test, features_dict, user_features_dict, full=True)
train_loader_smp = DataLoader(train_smp, BATCH_SIZE, num_workers=4)
test_loader = DataLoader(test, BATCH_SIZE, num_workers=1)
val_stats = run_epoch(
target,
test_loader,
[
Loss(),
RR(5),
MAP(3), MAP(5),
NDCG(3), NDCG(5),
HR(3), HR(5)
],
1
)
print(val_stats)
model = RankingAwareNet(SAF()).to(DEVICE)
target = RankingAwareNet(SAF()).to(DEVICE)
enc_opt = torch.optim.Adam(model.encoder.parameters())
opt = torch.optim.Adam(model.parameters())
best_acc = -1
train = get_train_instances(train_raw, user_features_dict, features_dict)
for epoch in range(EPOCHES):
train_loader = DataLoader(train, BATCH_SIZE, num_workers=2, shuffle=True)
ent_stats = run_epoch(model.encoder, train_loader, [Loss()], epoch, enc_opt)
train_sub = TruncatedIter(train_loader_smp, train_smp.__length_hint__() // BATCH_SIZE + 1)
frt_stats = run_epoch(model, train_sub, [Loss()], epoch, opt)
lerp = epoch / (epoch + 1)
with torch.no_grad():
target.load_state_dict(merge_state_dicts([
scale_state_dict(target.state_dict(), lerp),
scale_state_dict(model.state_dict(), 1 - lerp)
]))
val_stats = run_epoch(
target,
test_loader,
[
Loss(),
RR(5),
MAP(3), MAP(5),
NDCG(3), NDCG(5),
HR(3), HR(5)
],
epoch
)
if epoch == 0:
write_log(
"epoch",
"encoder_loss", "finetune_loss", "val_loss",
"val_rr@5",
"val_map@3", "val_map@5",
"val_ndcg@3", "val_ndcg@5",
"val_hr@3", "val_hr@5"
)
write_log(
epoch,
ent_stats['Loss'], frt_stats['Loss'], val_stats['Loss'],
val_stats['RR@5'],
val_stats['MAP@3'], val_stats['MAP@5'],
val_stats['NDCG@3'], val_stats['NDCG@5'],
val_stats['HR@3'], val_stats['HR@5']
)
if val_stats['NDCG@3'] > best_acc:
best_acc = val_stats['NDCG@3']
torch.save(model.state_dict(), "e2e.dat")
print("New best!")
if __name__ == "__main__":
main()
| import copy
import pickle
import random
import itertools
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy
from typing import Dict, List
from torch.utils.data import DataLoader, IterableDataset
from freq_counter import FreqCounter
from argparse import ArgumentParser
from baseline.metric import batch_ndcg_torch, batched_average_precision, batched_hit_ratio, batched_reciprocal_rank
import data_io
from common import *
from metrics import MAP, NDCG, HR, RR, Loss
def parse_args():
parser = ArgumentParser()
parser.add_argument(
'--epoch', '-e', type=int, default=20,
help='Number of training epoches')
parser.add_argument(
'--batchsize', '-b', type=int, default=64,
help='Batch size')
parser.add_argument(
'--dataset', '-d', choices=['bookcross', 'music'],
default='bookcross',
help='Dataset, can be one of bobookcrossok or music')
parser.add_argument(
'--device', type=str, default='cuda:0',
help='PyTorch style device to run the model')
return parser.parse_args()
def prepare_dataset(dataset: str):
assert dataset in ['bookcross', 'music'], f'Invalid dataset: {dataset}'
train_raw = data_io.load_rating_file_as_matrix(f'data/{dataset}.train.rating')
train_smp = data_io.load_train_entries(f'data/{dataset}.train.rating')
test = data_io.load_test_entries(f'data/{dataset}', False)
if dataset == 'bookcross':
feature_dict_path = 'data/book_info_bookcross'
user_feat_path = 'data/user_hist_withinfo_bookcross'
else:
feature_dict_path = 'data/song_info_music_HK'
user_feat_path = 'data/user_hist_withinfo_music_HK'
features_dict = pickle.load(open(feature_dict_path, 'rb'))
user_features_dict = pickle.load(open(user_feat_path, 'rb'))
return train_raw, train_smp, test, features_dict, user_features_dict
class SelfAttention(nn.Module):
def __init__(self, nhead, i, kq, v):
super().__init__()
self.attn_k = nn.Linear(i, kq, bias=False)
self.attn_q = nn.Linear(i, kq, bias=False)
self.attn_v = nn.Linear(i, v, bias=False)
self.nhead = nhead
def forward(self, x):
# x: ...ni
k = self.attn_k(x).reshape(*x.shape[:-1], self.nhead, -1)
q = self.attn_q(x).reshape(*x.shape[:-1], self.nhead, -1)
v = self.attn_v(x).reshape(*x.shape[:-1], self.nhead, -1)
attn = torch.softmax(
torch.einsum("...nhd,...mhd->...nmh", k, q) / k.shape[-1] ** 0.5,
-2
)
return torch.einsum("...nmh,...mhd->...nhd", attn, v).flatten(-2)
class SAF(nn.Module):
def __init__(self):
super().__init__()
self.user_embed = nn.Embedding(90000, 300)
self.item_embed = nn.Embedding(90000, 300)
with torch.no_grad():
self.user_embed.weight.uniform_(-0.05, 0.05)
self.item_embed.weight.uniform_(-0.05, 0.05)
self.attn = SelfAttention(5, 300, 600, 600)
self.drop = nn.Dropout(0.4)
self.proj = nn.Linear(600, 300)
self.linear = nn.Linear(300, 1)
self.norm = nn.LayerNorm(300)
def encode(self, user_features, item_features):
# bNMd
item = self.item_embed(item_features)
# bL4d
user = self.user_embed(user_features).mean(2) # bLd
user = user.unsqueeze(1).repeat(1, item.shape[1], 1, 1) # bNLd
sa_pre = torch.cat([user, item], 2) # bN (L+M) d
sa_post = self.norm(self.proj(self.attn(sa_pre)) + sa_pre).mean(-2) # bNd
return sa_post
def forward(self, user_ids, item_ids, user_features, item_features, labels=None):
sa_post = self.encode(user_features, item_features)
return self.linear(self.drop(sa_post)).squeeze()
class RankingAwareNet(nn.Module):
def __init__(self, encoder: SAF):
super().__init__()
self.encoder = encoder
self.impf = nn.Sequential(
nn.Linear(300, 1024),
nn.LayerNorm(1024), nn.ReLU(),
)
self.cls = nn.Sequential(
nn.Dropout(), nn.Linear(1324, 1)
)
def forward(self, user_ids, item_ids, user_features, item_features, labels=None):
with torch.no_grad():
sa_post = self.encoder.encode(user_features, item_features)
impf = self.impf(sa_post).max(-2)[0].unsqueeze(-2).repeat(1, sa_post.shape[1], 1)
pf = torch.cat([impf, sa_post], dim=-1)
return self.cls(pf).squeeze()
def get_train_instances(train, ufd, ifd):
user_input, item_input, labels = [], [], []
user_ids = []
item_ids = []
for (u, i) in train.keys():
user_ids.append(u)
item_ids.append(i)
user_input.append(numpy.array(ufd[u]).reshape(-1, 4))
item_input.append(numpy.array(ifd[i][:4])[None])
if train[(u, i)] == 1:
labels.append(1)
if train[(u, i)] == -1:
labels.append(0)
return [*zip(user_ids, item_ids, user_input, item_input, labels)]
class Rekommand(IterableDataset):
def __init__(
self, entries: List[data_io.TestEntry],
item_feature_dict: Dict[int, List[int]],
user_feature_dict: Dict[int, List[int]],
pos_per_entry: int = 5, neg_per_entry: int = 50,
background_neg_samples: int = 0,
full: bool = False
) -> None:
super().__init__()
self.full = full
self.ppe = pos_per_entry
self.npe = neg_per_entry
self.bns = background_neg_samples
self.entries = entries
self.ifd = item_feature_dict
self.ufd = user_feature_dict
self.valid_items = list(self.ifd.keys())
self.cum_weights = [*itertools.accumulate(map(
lambda x: len(x.positives) + len(x.negatives), self.entries
))]
def __iter__(self):
rng = len(self.entries) if self.full else 2 ** 30
for i in range(rng):
entry = self.entries[i] if self.full else\
random.choices(self.entries, cum_weights=self.cum_weights, k=1)[0]
entry = copy.deepcopy(entry)
if not self.full:
if not len(entry.positives):
continue
entry.positives = random.choices(entry.positives, k=self.ppe)
# entry.negatives = random.choices(entry.negatives, k=self.npe)
entry.negatives = random.choices(self.valid_items, k=self.npe)
items = numpy.array(list(entry.positives) + list(entry.negatives))
item_features = numpy.array([self.ifd[x][:4] for x in items])
user_features = numpy.array(self.ufd[entry.id]).reshape(-1, 4)
labels = numpy.concatenate([
numpy.ones_like(entry.positives),
numpy.zeros_like(entry.negatives)
])
randperm = numpy.random.permutation(len(items))
yield entry.id, items[randperm], user_features, item_features[randperm], labels[randperm]
def __length_hint__(self):
return len(self.entries) if self.full else 2 * len(self.entries)
def main():
args = parse_args()
DEVICE = torch.device(args.device)
BATCH_SIZE = args.batchsize
EPOCHES = args.epoch
train_raw, train_smp, test, features_dict, user_features_dict = prepare_dataset(args.dataset)
target = FreqCounter(train_smp)
train_smp = Rekommand(train_smp, features_dict, user_features_dict)
test = Rekommand(test, features_dict, user_features_dict, full=True)
train_loader_smp = DataLoader(train_smp, BATCH_SIZE, num_workers=4)
test_loader = DataLoader(test, BATCH_SIZE, num_workers=1)
val_stats = run_epoch(
target,
test_loader,
[
Loss(),
RR(5),
MAP(3), MAP(5),
NDCG(3), NDCG(5),
HR(3), HR(5)
],
1
)
print(val_stats)
model = RankingAwareNet(SAF()).to(DEVICE)
target = RankingAwareNet(SAF()).to(DEVICE)
enc_opt = torch.optim.Adam(model.encoder.parameters())
opt = torch.optim.Adam(model.parameters())
best_acc = -1
train = get_train_instances(train_raw, user_features_dict, features_dict)
for epoch in range(EPOCHES):
train_loader = DataLoader(train, BATCH_SIZE, num_workers=2, shuffle=True)
ent_stats = run_epoch(model.encoder, train_loader, [Loss()], epoch, enc_opt)
train_sub = TruncatedIter(train_loader_smp, train_smp.__length_hint__() // BATCH_SIZE + 1)
frt_stats = run_epoch(model, train_sub, [Loss()], epoch, opt)
lerp = epoch / (epoch + 1)
with torch.no_grad():
target.load_state_dict(merge_state_dicts([
scale_state_dict(target.state_dict(), lerp),
scale_state_dict(model.state_dict(), 1 - lerp)
]))
val_stats = run_epoch(
target,
test_loader,
[
Loss(),
RR(5),
MAP(3), MAP(5),
NDCG(3), NDCG(5),
HR(3), HR(5)
],
epoch
)
if epoch == 0:
write_log(
"epoch",
"encoder_loss", "finetune_loss", "val_loss",
"val_rr@5",
"val_map@3", "val_map@5",
"val_ndcg@3", "val_ndcg@5",
"val_hr@3", "val_hr@5"
)
write_log(
epoch,
ent_stats['Loss'], frt_stats['Loss'], val_stats['Loss'],
val_stats['RR@5'],
val_stats['MAP@3'], val_stats['MAP@5'],
val_stats['NDCG@3'], val_stats['NDCG@5'],
val_stats['HR@3'], val_stats['HR@5']
)
if val_stats['NDCG@3'] > best_acc:
best_acc = val_stats['NDCG@3']
torch.save(model.state_dict(), "e2e.dat")
print("New best!")
if __name__ == "__main__":
main() | en | 0.322257 | # x: ...ni # bNMd # bL4d # bLd # bNLd # bN (L+M) d # bNd # entry.negatives = random.choices(entry.negatives, k=self.npe) | 2.04019 | 2 |
alexa/fetcher.py | InfernapeXavier/song-match | 0 | 6620584 | <filename>alexa/fetcher.py
from pathlib import Path # python3 only
from spotipy.oauth2 import SpotifyClientCredentials
import spotipy
import sys
from dotenv import load_dotenv
# Loading Spotify API Data from Env
load_dotenv()
# spotipy credentials manager
sp = spotipy.Spotify(client_credentials_manager=SpotifyClientCredentials())
def songFetcher(artistName):
# Fetches top 10 songs by artistName
# Query to getartist URI
results = sp.search(q='artist:' + artistName, type='artist')
items = results['artists']['items']
if len(items) > 0:
artist = items[0]
urn = artist['uri']
# Query to fetch top tracks
response = sp.artist_top_tracks(urn)
trackList = []
for track in response['tracks']:
trackList.append(track['name'])
return trackList
def getIndex(score):
if score == '111':
return 0
if score == '112':
return 1
if score == '121':
return 2
if score == '122':
return 3
if score == '211':
return 4
if score == '212':
return 5
if score == '221':
return 6
if score == '222':
return 7
| <filename>alexa/fetcher.py
from pathlib import Path # python3 only
from spotipy.oauth2 import SpotifyClientCredentials
import spotipy
import sys
from dotenv import load_dotenv
# Loading Spotify API Data from Env
load_dotenv()
# spotipy credentials manager
sp = spotipy.Spotify(client_credentials_manager=SpotifyClientCredentials())
def songFetcher(artistName):
# Fetches top 10 songs by artistName
# Query to getartist URI
results = sp.search(q='artist:' + artistName, type='artist')
items = results['artists']['items']
if len(items) > 0:
artist = items[0]
urn = artist['uri']
# Query to fetch top tracks
response = sp.artist_top_tracks(urn)
trackList = []
for track in response['tracks']:
trackList.append(track['name'])
return trackList
def getIndex(score):
if score == '111':
return 0
if score == '112':
return 1
if score == '121':
return 2
if score == '122':
return 3
if score == '211':
return 4
if score == '212':
return 5
if score == '221':
return 6
if score == '222':
return 7
| en | 0.757608 | # python3 only # Loading Spotify API Data from Env # spotipy credentials manager # Fetches top 10 songs by artistName # Query to getartist URI # Query to fetch top tracks | 2.98893 | 3 |
demo/models/function/non_null_count.py | renovate-tests/django-check-constraint | 1 | 6620585 | from django.db.models import Func, SmallIntegerField, TextField
from django.db.models.functions import Cast
class NotNullCount(Func):
function = "non_null_count"
def __init__(self, *expressions, **extra):
filter_exp = [
Cast(exp, TextField()) for exp in expressions if isinstance(exp, str)
]
if "output_field" not in extra:
extra["output_field"] = SmallIntegerField()
if len(expressions) < 2:
raise ValueError("NotNullCount must take at least two expressions")
super().__init__(*filter_exp, **extra)
def as_sqlite(self, compiler, connection, **extra_context):
connection.ops.check_expression_support(self)
sql_parts = []
params = []
for arg in self.source_expressions:
arg_sql, arg_params = compiler.compile(arg)
sql_parts.append(arg_sql)
params.extend(arg_params)
data = {**self.extra, **extra_context}
data["template"] = "%(function)s(%(expressions)s)"
arg_joiner = self.arg_joiner
data["function"] = self.function
data["expressions"] = data["field"] = arg_joiner.join(sql_parts)
template = data["template"]
return template % data, params
| from django.db.models import Func, SmallIntegerField, TextField
from django.db.models.functions import Cast
class NotNullCount(Func):
function = "non_null_count"
def __init__(self, *expressions, **extra):
filter_exp = [
Cast(exp, TextField()) for exp in expressions if isinstance(exp, str)
]
if "output_field" not in extra:
extra["output_field"] = SmallIntegerField()
if len(expressions) < 2:
raise ValueError("NotNullCount must take at least two expressions")
super().__init__(*filter_exp, **extra)
def as_sqlite(self, compiler, connection, **extra_context):
connection.ops.check_expression_support(self)
sql_parts = []
params = []
for arg in self.source_expressions:
arg_sql, arg_params = compiler.compile(arg)
sql_parts.append(arg_sql)
params.extend(arg_params)
data = {**self.extra, **extra_context}
data["template"] = "%(function)s(%(expressions)s)"
arg_joiner = self.arg_joiner
data["function"] = self.function
data["expressions"] = data["field"] = arg_joiner.join(sql_parts)
template = data["template"]
return template % data, params
| none | 1 | 2.451294 | 2 | |
battlebuild.py | manhon95/QMG_bot | 0 | 6620586 | <gh_stars>0
import telegram
import sqlite3
import function
import thread_lock
import status_handler
from telegram import InlineKeyboardButton, InlineKeyboardMarkup
from telegram.ext import Updater, CommandHandler, CallbackQueryHandler, MessageHandler, Filters
#------------------------------------------Battle------------------------------------------
def battle_info(bot, country, space_list, card_id, lock_id, session):
print('battle info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
session.space_list_buffer = space_list
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = 'Choose a space to battle'
keyboard = []
for space in name_list:
piece_list = db.execute("select country.name from piece inner join country on piece.control = country.id where piece.location = :location and piece.type != 'air';", {'location':space[0]}).fetchall()
if len(piece_list) == 0:
keyboard.append([InlineKeyboardButton(space[1] + " - empty", callback_data="['battle', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))])
else:
button = space[1] + " - "
for piece in piece_list:
button += piece[0] + " "
keyboard.append([InlineKeyboardButton(button, callback_data="['battle', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))])
keyboard.append([InlineKeyboardButton('Pass', callback_data="['battle', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def battle_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
battle(bot, query_list[1], query_list[3], query_list[4], query_list[5], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = battle_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Battle ' + location[0][0] + ':'
piece_list = db.execute("select country.name, piece.pieceid from piece inner join country on piece.control = country.id where piece.location = :location and piece.type != 'air';", {'location':query_list[2]}).fetchall()
if len(piece_list) == 0:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['battle', '{}', 'confirm', 0, {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
elif len(piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['battle', '{}', 'confirm', {}, {}, {}, {}]".format(query_list[1], piece_list[0][1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
else:
keyboard = [[InlineKeyboardButton(piece[0], callback_data="['battle', '{}', 'confirm', {}, {}, {}, {}]".format(query_list[1], piece[1], query_list[2], query_list[3], query_list[-1]))] for piece in piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
def battle(bot, active_country, piece, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
passive_country = db.execute("select control from piece where pieceid = :piece;", {'piece':piece}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if piece == 0:
db.execute("update piece set location = :space where pieceid = :piece;", {'space':space, 'piece':piece})
db.commit()
text =" Empty space " + space_name[0][0] + " is battled by " + active_country_name[0][0]
else:
country_name = db.execute("select id, name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
status_handler.status_battle_handler(bot, active_country, country_name[0][0], space, session)
if db.execute("select noremove from piece where pieceid = :piece;", {'piece':piece}).fetchall()[0][0] == 0:
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][1] + " piece in " + space_name[0][0] + " is battled by " + active_country_name[0][0]
else:
text = country_name[0][1] + " piece in " + space_name[0][0] + " is not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Battle', lock_id, session, passive_country_id = passive_country[0][0], piece_id = piece, space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Remove------------------------------------------
class remove_obj():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.remove_id = len(session.remove_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "remove buffer add: "
info_list = {"remove_id":self.remove_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def remove_info(self, session):
db = sqlite3.connect(session.get_db_dir())
print('remove info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Choose a space to remove'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['remove', {}, {}]".format(space[0], self.remove_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['remove','pass', {}]".format(self.remove_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def remove_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[2]
remove(bot, self.country, self.piece_id, self.space_id, self.card_id, session)
session.release_lock(self.lock_id)
session.remove_list.pop(self.remove_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.remove_list.pop(self.remove_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.remove_info(session)
text = info[2]
reply_markup = info[3]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Remove ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select country.name, piece.pieceid, piece.type from piece inner join country on piece.control = country.id where piece.location = :location;", {'location':self.space_id}).fetchall()
else:
self.piece_list = db.execute("select country.name, piece.pieceid, piece.type from piece inner join country on piece.control = country.id where piece.location = :location and piece.type = :type;", {'location':self.space_id, 'type':self.piece_type}).fetchall()
if len(self.piece_list) == 0:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['remove', 'confirm', 0, {}]".format(self.remove_id))],
[InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format(self.remove_id))]]
elif len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['remove', 'confirm', {}, {}]".format(self.piece_list[0][1], self.remove_id))],
[InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format(self.remove_id))]]
else:
keyboard = [[InlineKeyboardButton(piece[0] + function.piece_type_name[piece[2]], callback_data="['remove', 'confirm', {}, {}]".format(piece[1], self.remove_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format((self.remove_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
def remove(bot, active_country, piece, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
piece_type = db.execute("select type from piece where pieceid = :piece;", {'piece':piece}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if piece == 0:
db.execute("update piece set location = :space where pieceid = :piece;", {'space':space, 'piece':piece})
db.commit()
text =" Empty space " + space_name[0][0] + " is removed by " + active_country_name[0][0]
else:
country_name = db.execute("select name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
if db.execute("select noremove from piece where pieceid = :piece;", {'piece':piece}).fetchall()[0][0] == 0:
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][0] + " " + function.piece_type_name[piece_type[0][0]] + " in " + space_name[0][0] + " is removed by " + active_country_name[0][0]
else:
text = country_name[0][0] + " piece in " + space_name[0][0] + " is not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Remove', lock_id, session, piece_id = piece, space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Self_Remove------------------------------------------
class self_remove():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.self_remove_id = len(session.self_remove_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "self_remove buffer add: "
info_list = {"self_remove_id":self.self_remove_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def self_remove_info(self, session):
db = sqlite3.connect(session.get_db_dir())
print('self_remove info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
print(name_list)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Choose a space to remove'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['self_remove', {}, {}]".format(space[0], self.self_remove_id))] for space in name_list]
#keyboard.append([InlineKeyboardButton('Pass', callback_data="['self_remove','pass', {}]".format(self.self_remove_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def self_remove_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[2]
remove(bot, self.country, self.piece_id, self.space_id, self.card_id, session)
session.release_lock(self.lock_id)
session.self_remove_list.pop(self.self_remove_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.self_remove_list.pop(self.self_remove_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.self_remove_info(session)
text = info[1]
reply_markup = info[2]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Remove ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select pieceid, type from piece where location = :location and control = :country;", {'location':self.space_id, 'country':self.country}).fetchall()
else:
self.piece_list = db.execute("select pieceid, type from piece where location = :location and type = :type and control = :country;", {'location':self.space_id, 'type':self.piece_type, 'country':self.country}).fetchall()
if len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['self_remove', 'confirm', {}, {}]".format(self.piece_list[0][0], self.self_remove_id))],
[InlineKeyboardButton('Back', callback_data="['self_remove', 'back', {}]".format(self.self_remove_id))]]
else:
keyboard = [[InlineKeyboardButton(function.piece_type_name[piece[1]], callback_data="['self_remove', 'confirm', {}, {}]".format(piece[0], self.self_remove_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['self_remove', 'back', {}]".format((self.self_remove_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
#------------------------------------------Move------------------------------------------
class move_obj():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.move_id = len(session.move_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "move buffer add: "
info_list = {"move_id":self.move_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def move_info(self, db):
print('move info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
print(name_list)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Pick up a piece:'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['move', {}, {}]".format(space[0], self.move_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['move','pass', {}]".format(self.move_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def move_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[3]
move(bot, self.country, self.piece_id, self.space_id, session)
session.release_lock(self.lock_id)
session.move_list.pop(self.move_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.move_list.pop(self.move_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.move_info(db)
text = info[2]
reply_markup = info[3]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Pick up piece in ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select pieceid, type from piece where location = :location;", {'location':self.space_id}).fetchall()
else:
self.piece_list = db.execute("select pieceid from piece where location = :location and type = :type;", {'location':self.space_id, 'type':self.piece_type}).fetchall()
if len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['move', 'confirm', {}, {}]".format(self.piece_list[0][0], self.move_id))],
[InlineKeyboardButton('Back', callback_data="['move', 'back', {}]".format(self.move_id))]]
else:
keyboard = [[InlineKeyboardButton(piece[1], callback_data="['move', 'confirm', {}, {}]".format(piece[1], self.move_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['move', 'back', {}]".format((self.move_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
def move(bot, active_country, piece, space, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
country_name = db.execute("select name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][0] + " piece in " + space_name[0][0] + " is picked up by " + active_country_name[0][0]
function.updatecontrol(bot, db)
import air
air.check_reposition(bot, session)
bot.send_message(chat_id = group_chat[0][0], text = text)
#------------------------------------------Build------------------------------------------
def build_info(bot, country, space_list, card_id, lock_id, session):
print('build info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
session.space_list_buffer = space_list
remain_army_count = db.execute("select count(*) from piece where control = :country and type = 'army' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_navy_count = db.execute("select count(*) from piece where control = :country and type = 'navy' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_air_count = db.execute("select count(*) from piece where control = :country and type = 'air' and location = 'none';", {'country':country}).fetchall()[0][0]
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = "Choose a space to build\n"
text += "Remain army:" + str(remain_army_count) + "\n"
text += "Remain navy:" + str(remain_navy_count) + "\n"
text += "Remain air force:" + str(remain_air_count) + "\n"
keyboard = [[InlineKeyboardButton(space[1], callback_data="['build', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['build', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def build_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
build(bot,query_list[1], query_list[3], query_list[4], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = build_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Build in ' + location[0][0] + ':'
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['build', '{}', 'confirm', {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['build', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text = text, reply_markup = reply_markup)
db.commit()
def build(bot, active_country, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if over_build_handler(bot, active_country, space_info[0][1], session):
text = active_country_name[0][0] + " do not remove piece to build"
bot.send_message(chat_id = group_chat[0][0], text = text)
else:
status_handler.status_build_handler(bot, active_country, session)
piece = db.execute("select min(pieceid) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_info[0][1]]}).fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece[0][0]})
text = active_country_name[0][0] + " build in " + space_info[0][0]
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
function.updatesupply(db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Build', lock_id, session, piece_id = piece[0][0], space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Recuit------------------------------------------
def recuit_info(bot, country, space_list, card_id, lock_id, session):
print('recuit info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
remain_army_count = db.execute("select count(*) from piece where control = :country and type = 'army' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_navy_count = db.execute("select count(*) from piece where control = :country and type = 'navy' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_air_count = db.execute("select count(*) from piece where control = :country and type = 'air' and location = 'none';", {'country':country}).fetchall()[0][0]
session.space_list_buffer = space_list
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = "Choose a space to recuit\n"
text += "Remain army:" + str(remain_army_count) + "\n"
text += "Remain navy:" + str(remain_navy_count) + "\n"
text += "Remain air force:" + str(remain_air_count) + "\n"
keyboard = [[InlineKeyboardButton(space[1], callback_data="['recuit', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['recuit', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def recuit_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
recuit(bot,query_list[1], query_list[3], query_list[4], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = recuit_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Recuit in ' + location[0][0] + ':'
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['recuit', '{}', 'confirm', {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['recuit', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text = text, reply_markup = reply_markup)
db.commit()
def recuit(bot, active_country, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if over_build_handler(bot, active_country, space_info[0][1], session):
text = active_country_name[0][0] + " do not remove piece to recuit"
bot.send_message(chat_id = group_chat[0][0], text = text)
else:
status_handler.status_recuit_handler(bot, active_country, session)
piece = db.execute("select min(pieceid) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_info[0][1]]}).fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece[0][0]})
text = active_country_name[0][0] + " recuit in " + space_info[0][0]
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
function.updatesupply(db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Recruit', lock_id, session, piece_id = piece[0][0], space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Over_Build_Handler------------------------------------------
def over_build_handler(bot, active_country, space_type, session):
db = sqlite3.connect(session.get_db_dir())
if db.execute("select count(*) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_type]}).fetchall()[0][0] == 0:
lock_id = session.add_lock()
space_list = function.control_space_list(active_country, db, space_type = space_type)
session.self_remove_list.append(self_remove(active_country, space_list, None, lock_id, function.terrain2type[space_type], session))
self_remove_id = len(session.self_remove_list)-1
info = session.self_remove_list[self_remove_id].self_remove_info(session)
bot.send_message(chat_id = info[0], text = info[1], reply_markup = info[2])
session.thread_lock(lock_id)
return (db.execute("select count(*) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_type]}).fetchall()[0][0] == 0)
#------------------------------------------Restore------------------------------------------
def restore(bot, piece, space, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece})
function.updatecontrol(bot, db)
import air
air.check_reposition(bot, session)
text = "Piece in " + space_info[0][0] + " not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
db.commit()
| import telegram
import sqlite3
import function
import thread_lock
import status_handler
from telegram import InlineKeyboardButton, InlineKeyboardMarkup
from telegram.ext import Updater, CommandHandler, CallbackQueryHandler, MessageHandler, Filters
#------------------------------------------Battle------------------------------------------
def battle_info(bot, country, space_list, card_id, lock_id, session):
print('battle info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
session.space_list_buffer = space_list
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = 'Choose a space to battle'
keyboard = []
for space in name_list:
piece_list = db.execute("select country.name from piece inner join country on piece.control = country.id where piece.location = :location and piece.type != 'air';", {'location':space[0]}).fetchall()
if len(piece_list) == 0:
keyboard.append([InlineKeyboardButton(space[1] + " - empty", callback_data="['battle', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))])
else:
button = space[1] + " - "
for piece in piece_list:
button += piece[0] + " "
keyboard.append([InlineKeyboardButton(button, callback_data="['battle', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))])
keyboard.append([InlineKeyboardButton('Pass', callback_data="['battle', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def battle_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
battle(bot, query_list[1], query_list[3], query_list[4], query_list[5], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = battle_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Battle ' + location[0][0] + ':'
piece_list = db.execute("select country.name, piece.pieceid from piece inner join country on piece.control = country.id where piece.location = :location and piece.type != 'air';", {'location':query_list[2]}).fetchall()
if len(piece_list) == 0:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['battle', '{}', 'confirm', 0, {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
elif len(piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['battle', '{}', 'confirm', {}, {}, {}, {}]".format(query_list[1], piece_list[0][1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
else:
keyboard = [[InlineKeyboardButton(piece[0], callback_data="['battle', '{}', 'confirm', {}, {}, {}, {}]".format(query_list[1], piece[1], query_list[2], query_list[3], query_list[-1]))] for piece in piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['battle', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
def battle(bot, active_country, piece, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
passive_country = db.execute("select control from piece where pieceid = :piece;", {'piece':piece}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if piece == 0:
db.execute("update piece set location = :space where pieceid = :piece;", {'space':space, 'piece':piece})
db.commit()
text =" Empty space " + space_name[0][0] + " is battled by " + active_country_name[0][0]
else:
country_name = db.execute("select id, name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
status_handler.status_battle_handler(bot, active_country, country_name[0][0], space, session)
if db.execute("select noremove from piece where pieceid = :piece;", {'piece':piece}).fetchall()[0][0] == 0:
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][1] + " piece in " + space_name[0][0] + " is battled by " + active_country_name[0][0]
else:
text = country_name[0][1] + " piece in " + space_name[0][0] + " is not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Battle', lock_id, session, passive_country_id = passive_country[0][0], piece_id = piece, space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Remove------------------------------------------
class remove_obj():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.remove_id = len(session.remove_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "remove buffer add: "
info_list = {"remove_id":self.remove_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def remove_info(self, session):
db = sqlite3.connect(session.get_db_dir())
print('remove info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Choose a space to remove'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['remove', {}, {}]".format(space[0], self.remove_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['remove','pass', {}]".format(self.remove_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def remove_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[2]
remove(bot, self.country, self.piece_id, self.space_id, self.card_id, session)
session.release_lock(self.lock_id)
session.remove_list.pop(self.remove_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.remove_list.pop(self.remove_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.remove_info(session)
text = info[2]
reply_markup = info[3]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Remove ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select country.name, piece.pieceid, piece.type from piece inner join country on piece.control = country.id where piece.location = :location;", {'location':self.space_id}).fetchall()
else:
self.piece_list = db.execute("select country.name, piece.pieceid, piece.type from piece inner join country on piece.control = country.id where piece.location = :location and piece.type = :type;", {'location':self.space_id, 'type':self.piece_type}).fetchall()
if len(self.piece_list) == 0:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['remove', 'confirm', 0, {}]".format(self.remove_id))],
[InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format(self.remove_id))]]
elif len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['remove', 'confirm', {}, {}]".format(self.piece_list[0][1], self.remove_id))],
[InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format(self.remove_id))]]
else:
keyboard = [[InlineKeyboardButton(piece[0] + function.piece_type_name[piece[2]], callback_data="['remove', 'confirm', {}, {}]".format(piece[1], self.remove_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['remove', 'back', {}]".format((self.remove_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
def remove(bot, active_country, piece, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
piece_type = db.execute("select type from piece where pieceid = :piece;", {'piece':piece}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if piece == 0:
db.execute("update piece set location = :space where pieceid = :piece;", {'space':space, 'piece':piece})
db.commit()
text =" Empty space " + space_name[0][0] + " is removed by " + active_country_name[0][0]
else:
country_name = db.execute("select name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
if db.execute("select noremove from piece where pieceid = :piece;", {'piece':piece}).fetchall()[0][0] == 0:
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][0] + " " + function.piece_type_name[piece_type[0][0]] + " in " + space_name[0][0] + " is removed by " + active_country_name[0][0]
else:
text = country_name[0][0] + " piece in " + space_name[0][0] + " is not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Remove', lock_id, session, piece_id = piece, space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Self_Remove------------------------------------------
class self_remove():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.self_remove_id = len(session.self_remove_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "self_remove buffer add: "
info_list = {"self_remove_id":self.self_remove_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def self_remove_info(self, session):
db = sqlite3.connect(session.get_db_dir())
print('self_remove info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
print(name_list)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Choose a space to remove'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['self_remove', {}, {}]".format(space[0], self.self_remove_id))] for space in name_list]
#keyboard.append([InlineKeyboardButton('Pass', callback_data="['self_remove','pass', {}]".format(self.self_remove_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def self_remove_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[2]
remove(bot, self.country, self.piece_id, self.space_id, self.card_id, session)
session.release_lock(self.lock_id)
session.self_remove_list.pop(self.self_remove_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.self_remove_list.pop(self.self_remove_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.self_remove_info(session)
text = info[1]
reply_markup = info[2]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Remove ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select pieceid, type from piece where location = :location and control = :country;", {'location':self.space_id, 'country':self.country}).fetchall()
else:
self.piece_list = db.execute("select pieceid, type from piece where location = :location and type = :type and control = :country;", {'location':self.space_id, 'type':self.piece_type, 'country':self.country}).fetchall()
if len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['self_remove', 'confirm', {}, {}]".format(self.piece_list[0][0], self.self_remove_id))],
[InlineKeyboardButton('Back', callback_data="['self_remove', 'back', {}]".format(self.self_remove_id))]]
else:
keyboard = [[InlineKeyboardButton(function.piece_type_name[piece[1]], callback_data="['self_remove', 'confirm', {}, {}]".format(piece[0], self.self_remove_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['self_remove', 'back', {}]".format((self.self_remove_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
#------------------------------------------Move------------------------------------------
class move_obj():
def __init__(self, country, space_list, card_id, lock_id, piece_type, session):
self.move_id = len(session.move_list)
self.country = country
self.space_list = space_list
self.card_id = card_id
self.lock_id = lock_id
self.piece_type = piece_type
self.space_id = None
self.piece_list = None
self.piece_id = None
text = "move buffer add: "
info_list = {"move_id":self.move_id, "country":country, "space_list":space_list, "card_id":card_id, "lock_id":lock_id, "piece_type":piece_type}
for info in info_list:
if info_list[info] != None:
text += " [" + info + ": " + str(info_list[info]) + "]"
print(text)
def move_info(self, db):
print('move info')
print(self.space_list)
name_list = function.get_name_list(self.space_list, db)
print(name_list)
chat_id = db.execute("select playerid from country where id = :country;", {'country':self.country}).fetchall()
text = 'Pick up a piece:'
keyboard = [[InlineKeyboardButton(space[1], callback_data="['move', {}, {}]".format(space[0], self.move_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['move','pass', {}]".format(self.move_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def move_cb(self, bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[1] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
self.piece_id = query_list[3]
move(bot, self.country, self.piece_id, self.space_id, session)
session.release_lock(self.lock_id)
session.move_list.pop(self.move_id)
elif query_list[1] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(self.lock_id)
session.move_list.pop(self.move_id)
else:
if query_list[1] == 'back':
self.space_id = None
info = self.move_info(db)
text = info[2]
reply_markup = info[3]
else:
self.space_id = query_list[1]
location = db.execute("select name from space where spaceid = :id", {'id':self.space_id}).fetchall()
text = 'Pick up piece in ' + location[0][0] + ':'
if self.piece_type == 'all':
self.piece_list = db.execute("select pieceid, type from piece where location = :location;", {'location':self.space_id}).fetchall()
else:
self.piece_list = db.execute("select pieceid from piece where location = :location and type = :type;", {'location':self.space_id, 'type':self.piece_type}).fetchall()
if len(self.piece_list) == 1:
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['move', 'confirm', {}, {}]".format(self.piece_list[0][0], self.move_id))],
[InlineKeyboardButton('Back', callback_data="['move', 'back', {}]".format(self.move_id))]]
else:
keyboard = [[InlineKeyboardButton(piece[1], callback_data="['move', 'confirm', {}, {}]".format(piece[1], self.move_id))] for piece in self.piece_list]
keyboard.append([InlineKeyboardButton('Back', callback_data="['move', 'back', {}]".format((self.move_id)))])
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text=text, reply_markup=reply_markup)
db.commit()
def move(bot, active_country, piece, space, session):
db = sqlite3.connect(session.get_db_dir())
function.updatesupply(db)
space_name = db.execute("select distinct name from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
country_name = db.execute("select name from country where id = (select control from piece where pieceid = :piece);", {'piece':piece}).fetchall()
db.execute("update piece set location = 'none' where pieceid = :piece;", {'piece':piece})
db.commit()
text = country_name[0][0] + " piece in " + space_name[0][0] + " is picked up by " + active_country_name[0][0]
function.updatecontrol(bot, db)
import air
air.check_reposition(bot, session)
bot.send_message(chat_id = group_chat[0][0], text = text)
#------------------------------------------Build------------------------------------------
def build_info(bot, country, space_list, card_id, lock_id, session):
print('build info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
session.space_list_buffer = space_list
remain_army_count = db.execute("select count(*) from piece where control = :country and type = 'army' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_navy_count = db.execute("select count(*) from piece where control = :country and type = 'navy' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_air_count = db.execute("select count(*) from piece where control = :country and type = 'air' and location = 'none';", {'country':country}).fetchall()[0][0]
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = "Choose a space to build\n"
text += "Remain army:" + str(remain_army_count) + "\n"
text += "Remain navy:" + str(remain_navy_count) + "\n"
text += "Remain air force:" + str(remain_air_count) + "\n"
keyboard = [[InlineKeyboardButton(space[1], callback_data="['build', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['build', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def build_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
build(bot,query_list[1], query_list[3], query_list[4], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = build_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Build in ' + location[0][0] + ':'
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['build', '{}', 'confirm', {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['build', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text = text, reply_markup = reply_markup)
db.commit()
def build(bot, active_country, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if over_build_handler(bot, active_country, space_info[0][1], session):
text = active_country_name[0][0] + " do not remove piece to build"
bot.send_message(chat_id = group_chat[0][0], text = text)
else:
status_handler.status_build_handler(bot, active_country, session)
piece = db.execute("select min(pieceid) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_info[0][1]]}).fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece[0][0]})
text = active_country_name[0][0] + " build in " + space_info[0][0]
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
function.updatesupply(db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Build', lock_id, session, piece_id = piece[0][0], space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Recuit------------------------------------------
def recuit_info(bot, country, space_list, card_id, lock_id, session):
print('recuit info')
print(space_list)
db = sqlite3.connect(session.get_db_dir())
name_list = function.get_name_list(space_list, db)
print(name_list)
remain_army_count = db.execute("select count(*) from piece where control = :country and type = 'army' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_navy_count = db.execute("select count(*) from piece where control = :country and type = 'navy' and location = 'none';", {'country':country}).fetchall()[0][0]
remain_air_count = db.execute("select count(*) from piece where control = :country and type = 'air' and location = 'none';", {'country':country}).fetchall()[0][0]
session.space_list_buffer = space_list
chat_id = db.execute("select playerid from country where id = :country;", {'country':country}).fetchall()
text = "Choose a space to recuit\n"
text += "Remain army:" + str(remain_army_count) + "\n"
text += "Remain navy:" + str(remain_navy_count) + "\n"
text += "Remain air force:" + str(remain_air_count) + "\n"
keyboard = [[InlineKeyboardButton(space[1], callback_data="['recuit', '{}', {}, {}, {}]".format(country, space[0], card_id, lock_id))] for space in name_list]
keyboard.append([InlineKeyboardButton('Pass', callback_data="['recuit', '{}', 'pass', {}, {}]".format(country, card_id, lock_id))])
reply_markup = InlineKeyboardMarkup(keyboard)
return chat_id[0][0], text, reply_markup
def recuit_cb(bot, query, query_list, session):
db = sqlite3.connect(session.get_db_dir())
if query_list[2] == 'confirm':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
recuit(bot,query_list[1], query_list[3], query_list[4], session)
session.release_lock(query_list[-1])
elif query_list[2] == 'pass':
bot.delete_message(chat_id = query.message.chat_id, message_id = query.message.message_id)
session.release_lock(query_list[-1])
else:
if query_list[2] == 'back':
info = recuit_info(bot, query_list[1] , session.space_list_buffer, query_list[3], query_list[-1], session)
text = info[1]
reply_markup = info[2]
else:
location = db.execute("select name from space where spaceid = :id", {'id':query_list[2]}).fetchall()
text = 'Recuit in ' + location[0][0] + ':'
keyboard = [[InlineKeyboardButton('Confirm', callback_data="['recuit', '{}', 'confirm', {}, {}, {}]".format(query_list[1], query_list[2], query_list[3], query_list[-1]))], [InlineKeyboardButton('Back', callback_data="['recuit', '{}', 'back', {}, {}]".format(query_list[1], query_list[3], query_list[-1]))]]
reply_markup = InlineKeyboardMarkup(keyboard)
bot.edit_message_text(chat_id=query.message.chat_id, message_id=query.message.message_id, text = text, reply_markup = reply_markup)
db.commit()
def recuit(bot, active_country, space, card_id, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
active_country_name = db.execute("select name from country where id = :country;", {'country':active_country}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
if over_build_handler(bot, active_country, space_info[0][1], session):
text = active_country_name[0][0] + " do not remove piece to recuit"
bot.send_message(chat_id = group_chat[0][0], text = text)
else:
status_handler.status_recuit_handler(bot, active_country, session)
piece = db.execute("select min(pieceid) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_info[0][1]]}).fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece[0][0]})
text = active_country_name[0][0] + " recuit in " + space_info[0][0]
bot.send_message(chat_id = group_chat[0][0], text = text)
function.updatecontrol(bot, db)
function.updatesupply(db)
lock_id = session.add_lock()
status_handler.send_status_card(bot, active_country, 'Recruit', lock_id, session, piece_id = piece[0][0], space_id = space, card_id = card_id)
import air
air.check_reposition(bot, session)
db.commit()
#------------------------------------------Over_Build_Handler------------------------------------------
def over_build_handler(bot, active_country, space_type, session):
db = sqlite3.connect(session.get_db_dir())
if db.execute("select count(*) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_type]}).fetchall()[0][0] == 0:
lock_id = session.add_lock()
space_list = function.control_space_list(active_country, db, space_type = space_type)
session.self_remove_list.append(self_remove(active_country, space_list, None, lock_id, function.terrain2type[space_type], session))
self_remove_id = len(session.self_remove_list)-1
info = session.self_remove_list[self_remove_id].self_remove_info(session)
bot.send_message(chat_id = info[0], text = info[1], reply_markup = info[2])
session.thread_lock(lock_id)
return (db.execute("select count(*) from piece where location = 'none' and control = :country and type = :piece_type;", {'country':active_country, 'piece_type':function.terrain2type[space_type]}).fetchall()[0][0] == 0)
#------------------------------------------Restore------------------------------------------
def restore(bot, piece, space, session):
db = sqlite3.connect(session.get_db_dir())
space_info = db.execute("select distinct name, type from space where spaceid = :space;", {'space':space}).fetchall()
group_chat = db.execute("select chatid from game;").fetchall()
db.execute("update piece set location = :location where pieceid = :piece;", {'location':space, 'piece':piece})
function.updatecontrol(bot, db)
import air
air.check_reposition(bot, session)
text = "Piece in " + space_info[0][0] + " not removed"
bot.send_message(chat_id = group_chat[0][0], text = text)
db.commit() | pt | 0.083994 | #------------------------------------------Battle------------------------------------------ #------------------------------------------Remove------------------------------------------ #------------------------------------------Self_Remove------------------------------------------ #keyboard.append([InlineKeyboardButton('Pass', callback_data="['self_remove','pass', {}]".format(self.self_remove_id))]) #------------------------------------------Move------------------------------------------ #------------------------------------------Build------------------------------------------ #------------------------------------------Recuit------------------------------------------ #------------------------------------------Over_Build_Handler------------------------------------------ #------------------------------------------Restore------------------------------------------ | 2.662015 | 3 |
AGV_emotions_attack/attacks_emotions/agv/log.py | Ellyuca/AGV-Project | 0 | 6620587 |
class Log(object):
def __init__(self, path, append=False):
self.f_log = open(path,"w" if not append else "a+")
def log(self, *args):
self.f_log.write(*args)
self.f_log.write("\n")
self.f_log.flush()
def close(self):
self.f_log.close()
def __del__(self):
self.f_log.close()
|
class Log(object):
def __init__(self, path, append=False):
self.f_log = open(path,"w" if not append else "a+")
def log(self, *args):
self.f_log.write(*args)
self.f_log.write("\n")
self.f_log.flush()
def close(self):
self.f_log.close()
def __del__(self):
self.f_log.close()
| none | 1 | 3.314954 | 3 | |
tests/test_converter.py | vyahello/calorie-counter | 5 | 6620588 | <reponame>vyahello/calorie-counter<filename>tests/test_converter.py
import os
import pytest
from counter.converter import csv_to_json
from counter.writer import write_to_file
_path: str = f"{os.path.join(os.path.dirname(__file__), 'test.csv')}"
@pytest.fixture(scope="module", autouse=True)
def setup_data() -> None:
write_to_file(
_path,
(
"Category,Item,Serving Size,Calories,Calories from Fat,"
"Total Fat,Total Fat (% Daily Value),Saturated Fat\n"
"Breakfast,Egg McMuffin,4.8 oz (136 g),300,120,13,20,5\n"
"Breakfast,Egg White Delight,4.8 oz (135 g),250,70,8,12,3\n"
),
mode="a",
)
yield
os.remove(_path)
def test_csv_to_json() -> None:
assert (
csv_to_json(_path)
== '{"Egg McMuffin [4.8 oz / 136 g]": "300", '
'"Egg White Delight [4.8 oz / 135 g]": "250"}'
)
| import os
import pytest
from counter.converter import csv_to_json
from counter.writer import write_to_file
_path: str = f"{os.path.join(os.path.dirname(__file__), 'test.csv')}"
@pytest.fixture(scope="module", autouse=True)
def setup_data() -> None:
write_to_file(
_path,
(
"Category,Item,Serving Size,Calories,Calories from Fat,"
"Total Fat,Total Fat (% Daily Value),Saturated Fat\n"
"Breakfast,Egg McMuffin,4.8 oz (136 g),300,120,13,20,5\n"
"Breakfast,Egg White Delight,4.8 oz (135 g),250,70,8,12,3\n"
),
mode="a",
)
yield
os.remove(_path)
def test_csv_to_json() -> None:
assert (
csv_to_json(_path)
== '{"Egg McMuffin [4.8 oz / 136 g]": "300", '
'"Egg White Delight [4.8 oz / 135 g]": "250"}'
) | none | 1 | 2.430977 | 2 | |
tests/utils/testAType.py | DedeKite/wxPlotLab | 6 | 6620589 | <reponame>DedeKite/wxPlotLab
# -*-coding:Utf-8 -*
import unittest
from mplotlab.utils.abctypes import LIST,\
STRING,\
COLOR,\
INT,\
BOOL
import numpy as np
class TestAType(unittest.TestCase):
def test_LIST(self):
ali = LIST()
l = ali.getBase()
l.append(BOOL(False))
l.append(INT(36))
msg=ali.tostringxml("mylist")
msgRef=\
"""<root><mylist type="LIST">"""+\
"""<elem type="BOOL">0</elem>"""+\
"""<elem type="INT">36</elem>"""+\
"""</mylist></root>"""
self.assertEqual(msgRef, msg)
if __name__ == '__main__':
unittest.main()
| # -*-coding:Utf-8 -*
import unittest
from mplotlab.utils.abctypes import LIST,\
STRING,\
COLOR,\
INT,\
BOOL
import numpy as np
class TestAType(unittest.TestCase):
def test_LIST(self):
ali = LIST()
l = ali.getBase()
l.append(BOOL(False))
l.append(INT(36))
msg=ali.tostringxml("mylist")
msgRef=\
"""<root><mylist type="LIST">"""+\
"""<elem type="BOOL">0</elem>"""+\
"""<elem type="INT">36</elem>"""+\
"""</mylist></root>"""
self.assertEqual(msgRef, msg)
if __name__ == '__main__':
unittest.main() | en | 0.303203 | # -*-coding:Utf-8 -* <root><mylist type="LIST"> <elem type="BOOL">0</elem> <elem type="INT">36</elem> </mylist></root> | 3.076659 | 3 |
bot.py | thinkzink/idiomata-bot | 0 | 6620590 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Simple Bot to reply to Telegram messages.
This is built on the API wrapper, see echobot2.py to see the same example built
on the telegram.ext bot framework.
This program is dedicated to the public domain under the CC0 license.
"""
import logging
import telegram
import mielke_tokenizer as tok
import lang_id
from telegram.error import NetworkError, Unauthorized
from time import sleep
from collections import defaultdict
update_id = None
user_stats = defaultdict(lambda: UserStats())
lang_ider = lang_id.WordCountBasedLanguageID()
class UserStats():
def __init__(self):
self.words_written = 0
self.words_in_lang = defaultdict(lambda: 0)
def main():
"""Run the bot."""
global update_id
# Telegram Bot Authorization Token
with open('token.txt', 'r') as f:
token = f.readline().strip()
bot = telegram.Bot(token)
# get the first pending update_id, this is so we can skip over it in case
# we get an "Unauthorized" exception.
try:
update_id = bot.get_updates()[0].update_id
except IndexError:
update_id = None
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
while True:
try:
echo(bot)
except NetworkError:
sleep(1)
except Unauthorized:
# The user has removed or blocked the bot.
update_id += 1
def echo(bot):
"""Echo the message the user sent."""
global update_id
# Request updates after the last update_id
for update in bot.get_updates(offset=update_id, timeout=10):
update_id = update.update_id + 1
if update.message: # your bot can receive updates without messages
# Reply to the message
user = update.effective_user
text = update.message.text
entities = update.message.parse_entities()
# Parse mentions
if '@IdiomataBot' in entities.values():
if 'my score' in text:
my_sum = float(sum(user_stats[user.id].words_in_lang.values()))
my_cnts = [(cnt/my_sum, word) for (word, cnt) in user_stats[user.id].words_in_lang.items() if cnt/my_sum > 0.01]
my_cnts.sort(reverse=True)
words_in_lang_string = ', '.join([f'{cnt*100:.1f}% words in {lang}' for (cnt, lang) in my_cnts])
update.message.reply_text(f'{user.first_name} has written {words_in_lang_string}')
else:
update.message.reply_text('Sorry, I couldn\'t recognize that command')
# Parse normal messages
else:
tokenized_message = tok.tokenize(str(text)).split()
user_stats[user.id].words_written += len(tokenized_message)
words = user_stats[user.id].words_written
word_langs = lang_ider.id_words(tokenized_message, id_type='name')
print(tokenized_message)
print(word_langs)
for word_lang in word_langs:
user_stats[user.id].words_in_lang[word_lang] += 1
if __name__ == '__main__':
main()
| #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Simple Bot to reply to Telegram messages.
This is built on the API wrapper, see echobot2.py to see the same example built
on the telegram.ext bot framework.
This program is dedicated to the public domain under the CC0 license.
"""
import logging
import telegram
import mielke_tokenizer as tok
import lang_id
from telegram.error import NetworkError, Unauthorized
from time import sleep
from collections import defaultdict
update_id = None
user_stats = defaultdict(lambda: UserStats())
lang_ider = lang_id.WordCountBasedLanguageID()
class UserStats():
def __init__(self):
self.words_written = 0
self.words_in_lang = defaultdict(lambda: 0)
def main():
"""Run the bot."""
global update_id
# Telegram Bot Authorization Token
with open('token.txt', 'r') as f:
token = f.readline().strip()
bot = telegram.Bot(token)
# get the first pending update_id, this is so we can skip over it in case
# we get an "Unauthorized" exception.
try:
update_id = bot.get_updates()[0].update_id
except IndexError:
update_id = None
logging.basicConfig(format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
while True:
try:
echo(bot)
except NetworkError:
sleep(1)
except Unauthorized:
# The user has removed or blocked the bot.
update_id += 1
def echo(bot):
"""Echo the message the user sent."""
global update_id
# Request updates after the last update_id
for update in bot.get_updates(offset=update_id, timeout=10):
update_id = update.update_id + 1
if update.message: # your bot can receive updates without messages
# Reply to the message
user = update.effective_user
text = update.message.text
entities = update.message.parse_entities()
# Parse mentions
if '@IdiomataBot' in entities.values():
if 'my score' in text:
my_sum = float(sum(user_stats[user.id].words_in_lang.values()))
my_cnts = [(cnt/my_sum, word) for (word, cnt) in user_stats[user.id].words_in_lang.items() if cnt/my_sum > 0.01]
my_cnts.sort(reverse=True)
words_in_lang_string = ', '.join([f'{cnt*100:.1f}% words in {lang}' for (cnt, lang) in my_cnts])
update.message.reply_text(f'{user.first_name} has written {words_in_lang_string}')
else:
update.message.reply_text('Sorry, I couldn\'t recognize that command')
# Parse normal messages
else:
tokenized_message = tok.tokenize(str(text)).split()
user_stats[user.id].words_written += len(tokenized_message)
words = user_stats[user.id].words_written
word_langs = lang_ider.id_words(tokenized_message, id_type='name')
print(tokenized_message)
print(word_langs)
for word_lang in word_langs:
user_stats[user.id].words_in_lang[word_lang] += 1
if __name__ == '__main__':
main()
| en | 0.732829 | #!/usr/bin/env python # -*- coding: utf-8 -*- Simple Bot to reply to Telegram messages. This is built on the API wrapper, see echobot2.py to see the same example built on the telegram.ext bot framework. This program is dedicated to the public domain under the CC0 license. Run the bot. # Telegram Bot Authorization Token # get the first pending update_id, this is so we can skip over it in case # we get an "Unauthorized" exception. # The user has removed or blocked the bot. Echo the message the user sent. # Request updates after the last update_id # your bot can receive updates without messages # Reply to the message # Parse mentions # Parse normal messages | 3.119707 | 3 |
dask_cuda/explicit_comms/dataframe/merge.py | Ethyling/dask-cuda | 0 | 6620591 | <gh_stars>0
import asyncio
from collections import defaultdict
from toolz import first
from dask import dataframe as dd
from dask.dataframe.core import _concat
from dask.dataframe.shuffle import partitioning_index, shuffle_group
from distributed.client import get_client, wait
from distributed.protocol import to_serialize
from .. import comms
async def send_df(ep, df):
if df is None:
return await ep.write(None)
else:
return await ep.write([to_serialize(df)])
async def recv_df(ep):
ret = await ep.read()
if ret is None:
return None
else:
return ret[0]
async def send_bins(eps, bins):
futures = []
for rank, ep in eps.items():
futures.append(send_df(ep, bins[rank]))
await asyncio.gather(*futures)
async def recv_bins(eps, bins):
futures = []
for ep in eps.values():
futures.append(recv_df(ep))
bins.extend(await asyncio.gather(*futures))
async def exchange_and_concat_bins(rank, eps, bins):
ret = [bins[rank]]
await asyncio.gather(recv_bins(eps, ret), send_bins(eps, bins))
return _concat([df for df in ret if df is not None])
def df_concat(df_parts):
"""Making sure df_parts is a single dataframe or None"""
if len(df_parts) == 0:
return None
elif len(df_parts) == 1:
return df_parts[0]
else:
return _concat(df_parts)
async def broadcast(rank, root_rank, eps, df=None):
if rank == root_rank:
await asyncio.gather(*[send_df(ep, df) for ep in eps.values()])
return df
else:
return await recv_df(eps[root_rank])
def partition_by_hash(df, columns, n_chunks, ignore_index=False):
"""Splits dataframe into partitions
The partitions is determined by the hash value of the rows in `columns`.
Parameters
----------
df: DataFrame
columns: label or list
Column names on which to split the dataframe
npartition: int
Number of partitions
ignore_index : bool, default False
Set True to ignore the index of `df`
Returns
-------
out: Dict[int, DataFrame]
A dictionary mapping integers in {0..npartition} to dataframes.
"""
if df is None:
return [None] * n_chunks
# Hashing `columns` in `df` and assign it to the "_partitions" column
df["_partitions"] = partitioning_index(df[columns], n_chunks)
# Split `df` based on the hash values in the "_partitions" column
try:
# For Dask < 2.17 compatibility
ret = shuffle_group(df, "_partitions", 0, n_chunks, n_chunks, ignore_index)
except TypeError:
ret = shuffle_group(
df, "_partitions", 0, n_chunks, n_chunks, ignore_index, n_chunks
)
# Let's remove the partition column and return the partitions
del df["_partitions"]
for df in ret.values():
del df["_partitions"]
return ret
async def hash_join(n_chunks, rank, eps, left_table, right_table, left_on, right_on):
left_bins = partition_by_hash(left_table, left_on, n_chunks, ignore_index=True)
left_df = exchange_and_concat_bins(rank, eps, left_bins)
right_bins = partition_by_hash(right_table, right_on, n_chunks, ignore_index=True)
left_df = await left_df
right_df = await exchange_and_concat_bins(rank, eps, right_bins)
return left_df.merge(right_df, left_on=left_on, right_on=right_on)
async def single_partition_join(
n_chunks,
rank,
eps,
left_table,
right_table,
left_on,
right_on,
single_table,
single_rank,
):
if single_table == "left":
left_table = await broadcast(rank, single_rank, eps, left_table)
else:
assert single_table == "right"
right_table = await broadcast(rank, single_rank, eps, right_table)
return left_table.merge(right_table, left_on=left_on, right_on=right_on)
async def local_df_merge(s, workers, dfs_nparts, dfs_parts, left_on, right_on):
"""Worker job that merge local DataFrames
Parameters
----------
s: dict
Worker session state
workers: set
Set of ranks of all the participants
dfs_nparts: list of dict
List of dict that for each worker rank specifices the
number of partitions that worker has. If the worker doesn't
have any partitions, it is excluded from the dict.
E.g. `dfs_nparts[0][1]` is how many partitions of the "left"
dataframe worker 1 has.
dfs_parts: list of lists of Dataframes
List of inputs, which in this case are two dataframe lists.
left_on : str or list of str
Column to join on in the left DataFrame.
right_on : str or list of str
Column to join on in the right DataFrame.
Returns
-------
df: DataFrame
Merged dataframe
"""
assert s["rank"] in workers
# Trimming such that all participanting workers get a rank within 0..len(workers)
trim_map = {}
for i in range(s["nworkers"]):
if i in workers:
trim_map[i] = len(trim_map)
rank = trim_map[s["rank"]]
eps = {trim_map[i]: s["eps"][trim_map[i]] for i in workers if i != s["rank"]}
df1 = df_concat(dfs_parts[0])
df2 = df_concat(dfs_parts[1])
if len(dfs_nparts[0]) == 1 and len(dfs_nparts[1]) == 1:
return df1.merge(df2, left_on=left_on, right_on=right_on)
elif len(dfs_nparts[0]) == 1:
return await single_partition_join(
len(workers),
rank,
eps,
df1,
df2,
left_on,
right_on,
"left",
trim_map[
next(iter(dfs_nparts[0]))
], # Extracting the only key in `dfs_nparts[0]`
)
elif len(dfs_nparts[1]) == 1:
return await single_partition_join(
len(workers),
rank,
eps,
df1,
df2,
left_on,
right_on,
"right",
trim_map[
next(iter(dfs_nparts[1]))
], # Extracting the only key in `dfs_nparts[1]`
)
else:
return await hash_join(len(workers), rank, eps, df1, df2, left_on, right_on)
def extract_ddf_partitions(ddf):
""" Returns the mapping: worker -> [list of futures]"""
client = get_client()
delayed_ddf = ddf.to_delayed()
parts = client.compute(delayed_ddf)
wait(parts)
key_to_part = dict([(str(part.key), part) for part in parts])
ret = defaultdict(list) # Map worker -> [list of futures]
for key, workers in client.who_has(parts).items():
worker = first(
workers
) # If multiple workers have the part, we pick the first worker
ret[worker].append(key_to_part[key])
return ret
def submit_dataframe_operation(comms, coroutine, df_list, extra_args=()):
"""Submit an operation on a list of Dask dataframe
Parameters
----------
coroutine: coroutine
The function to run on each worker.
df_list: list of Dask.dataframe.Dataframe
Input dataframes
extra_args: tuple
Extra function input
Returns
-------
dataframe: dask.dataframe.DataFrame
The resulting dataframe
"""
df_parts_list = []
for df in df_list:
df_parts_list.append(extract_ddf_partitions(df))
# Let's create a dict for each dataframe that specifices the
# number of partitions each worker has
world = set()
dfs_nparts = []
for df_parts in df_parts_list:
nparts = {}
for rank, worker in enumerate(comms.worker_addresses):
npart = len(df_parts.get(worker, []))
if npart > 0:
nparts[rank] = npart
world.add(rank)
dfs_nparts.append(nparts)
# Submit `coroutine` on each worker given the df_parts that
# belong the specific worker as input
ret = []
for rank, worker in enumerate(comms.worker_addresses):
if rank in world:
dfs = []
for df_parts in df_parts_list:
dfs.append(df_parts.get(worker, []))
ret.append(
comms.submit(worker, coroutine, world, dfs_nparts, dfs, *extra_args)
)
wait(ret)
return dd.from_delayed(ret)
def merge(left, right, on=None, left_on=None, right_on=None):
"""Merge two DataFrames using explicit-comms.
This is an explicit-comms version of Dask's Dataframe.merge() that
only supports "inner" joins.
Requires an activate client.
Notice
------
As a side effect, this operation concatenate all partitions located on
the same worker thus npartitions of the returned dataframe equals number
of workers.
Parameters
----------
left: dask.dataframe.DataFrame
right: dask.dataframe.DataFrame
on : str or list of str
Column or index level names to join on. These must be found in both
DataFrames.
left_on : str or list of str
Column to join on in the left DataFrame.
right_on : str or list of str
Column to join on in the right DataFrame.
Returns
-------
df: dask.dataframe.DataFrame
Merged dataframe
"""
# Making sure that the "on" arguments are list of column names
if on:
on = [on] if isinstance(on, str) else list(on)
if left_on:
left_on = [left_on] if isinstance(left_on, str) else list(left_on)
if right_on:
right_on = [right_on] if isinstance(right_on, str) else list(right_on)
if left_on is None:
left_on = on
if right_on is None:
right_on = on
if not (left_on and right_on):
raise ValueError(
"Some combination of the on, left_on, and right_on arguments must be set"
)
return submit_dataframe_operation(
comms.default_comms(),
local_df_merge,
df_list=(left, right),
extra_args=(left_on, right_on),
)
| import asyncio
from collections import defaultdict
from toolz import first
from dask import dataframe as dd
from dask.dataframe.core import _concat
from dask.dataframe.shuffle import partitioning_index, shuffle_group
from distributed.client import get_client, wait
from distributed.protocol import to_serialize
from .. import comms
async def send_df(ep, df):
if df is None:
return await ep.write(None)
else:
return await ep.write([to_serialize(df)])
async def recv_df(ep):
ret = await ep.read()
if ret is None:
return None
else:
return ret[0]
async def send_bins(eps, bins):
futures = []
for rank, ep in eps.items():
futures.append(send_df(ep, bins[rank]))
await asyncio.gather(*futures)
async def recv_bins(eps, bins):
futures = []
for ep in eps.values():
futures.append(recv_df(ep))
bins.extend(await asyncio.gather(*futures))
async def exchange_and_concat_bins(rank, eps, bins):
ret = [bins[rank]]
await asyncio.gather(recv_bins(eps, ret), send_bins(eps, bins))
return _concat([df for df in ret if df is not None])
def df_concat(df_parts):
"""Making sure df_parts is a single dataframe or None"""
if len(df_parts) == 0:
return None
elif len(df_parts) == 1:
return df_parts[0]
else:
return _concat(df_parts)
async def broadcast(rank, root_rank, eps, df=None):
if rank == root_rank:
await asyncio.gather(*[send_df(ep, df) for ep in eps.values()])
return df
else:
return await recv_df(eps[root_rank])
def partition_by_hash(df, columns, n_chunks, ignore_index=False):
"""Splits dataframe into partitions
The partitions is determined by the hash value of the rows in `columns`.
Parameters
----------
df: DataFrame
columns: label or list
Column names on which to split the dataframe
npartition: int
Number of partitions
ignore_index : bool, default False
Set True to ignore the index of `df`
Returns
-------
out: Dict[int, DataFrame]
A dictionary mapping integers in {0..npartition} to dataframes.
"""
if df is None:
return [None] * n_chunks
# Hashing `columns` in `df` and assign it to the "_partitions" column
df["_partitions"] = partitioning_index(df[columns], n_chunks)
# Split `df` based on the hash values in the "_partitions" column
try:
# For Dask < 2.17 compatibility
ret = shuffle_group(df, "_partitions", 0, n_chunks, n_chunks, ignore_index)
except TypeError:
ret = shuffle_group(
df, "_partitions", 0, n_chunks, n_chunks, ignore_index, n_chunks
)
# Let's remove the partition column and return the partitions
del df["_partitions"]
for df in ret.values():
del df["_partitions"]
return ret
async def hash_join(n_chunks, rank, eps, left_table, right_table, left_on, right_on):
left_bins = partition_by_hash(left_table, left_on, n_chunks, ignore_index=True)
left_df = exchange_and_concat_bins(rank, eps, left_bins)
right_bins = partition_by_hash(right_table, right_on, n_chunks, ignore_index=True)
left_df = await left_df
right_df = await exchange_and_concat_bins(rank, eps, right_bins)
return left_df.merge(right_df, left_on=left_on, right_on=right_on)
async def single_partition_join(
n_chunks,
rank,
eps,
left_table,
right_table,
left_on,
right_on,
single_table,
single_rank,
):
if single_table == "left":
left_table = await broadcast(rank, single_rank, eps, left_table)
else:
assert single_table == "right"
right_table = await broadcast(rank, single_rank, eps, right_table)
return left_table.merge(right_table, left_on=left_on, right_on=right_on)
async def local_df_merge(s, workers, dfs_nparts, dfs_parts, left_on, right_on):
"""Worker job that merge local DataFrames
Parameters
----------
s: dict
Worker session state
workers: set
Set of ranks of all the participants
dfs_nparts: list of dict
List of dict that for each worker rank specifices the
number of partitions that worker has. If the worker doesn't
have any partitions, it is excluded from the dict.
E.g. `dfs_nparts[0][1]` is how many partitions of the "left"
dataframe worker 1 has.
dfs_parts: list of lists of Dataframes
List of inputs, which in this case are two dataframe lists.
left_on : str or list of str
Column to join on in the left DataFrame.
right_on : str or list of str
Column to join on in the right DataFrame.
Returns
-------
df: DataFrame
Merged dataframe
"""
assert s["rank"] in workers
# Trimming such that all participanting workers get a rank within 0..len(workers)
trim_map = {}
for i in range(s["nworkers"]):
if i in workers:
trim_map[i] = len(trim_map)
rank = trim_map[s["rank"]]
eps = {trim_map[i]: s["eps"][trim_map[i]] for i in workers if i != s["rank"]}
df1 = df_concat(dfs_parts[0])
df2 = df_concat(dfs_parts[1])
if len(dfs_nparts[0]) == 1 and len(dfs_nparts[1]) == 1:
return df1.merge(df2, left_on=left_on, right_on=right_on)
elif len(dfs_nparts[0]) == 1:
return await single_partition_join(
len(workers),
rank,
eps,
df1,
df2,
left_on,
right_on,
"left",
trim_map[
next(iter(dfs_nparts[0]))
], # Extracting the only key in `dfs_nparts[0]`
)
elif len(dfs_nparts[1]) == 1:
return await single_partition_join(
len(workers),
rank,
eps,
df1,
df2,
left_on,
right_on,
"right",
trim_map[
next(iter(dfs_nparts[1]))
], # Extracting the only key in `dfs_nparts[1]`
)
else:
return await hash_join(len(workers), rank, eps, df1, df2, left_on, right_on)
def extract_ddf_partitions(ddf):
""" Returns the mapping: worker -> [list of futures]"""
client = get_client()
delayed_ddf = ddf.to_delayed()
parts = client.compute(delayed_ddf)
wait(parts)
key_to_part = dict([(str(part.key), part) for part in parts])
ret = defaultdict(list) # Map worker -> [list of futures]
for key, workers in client.who_has(parts).items():
worker = first(
workers
) # If multiple workers have the part, we pick the first worker
ret[worker].append(key_to_part[key])
return ret
def submit_dataframe_operation(comms, coroutine, df_list, extra_args=()):
"""Submit an operation on a list of Dask dataframe
Parameters
----------
coroutine: coroutine
The function to run on each worker.
df_list: list of Dask.dataframe.Dataframe
Input dataframes
extra_args: tuple
Extra function input
Returns
-------
dataframe: dask.dataframe.DataFrame
The resulting dataframe
"""
df_parts_list = []
for df in df_list:
df_parts_list.append(extract_ddf_partitions(df))
# Let's create a dict for each dataframe that specifices the
# number of partitions each worker has
world = set()
dfs_nparts = []
for df_parts in df_parts_list:
nparts = {}
for rank, worker in enumerate(comms.worker_addresses):
npart = len(df_parts.get(worker, []))
if npart > 0:
nparts[rank] = npart
world.add(rank)
dfs_nparts.append(nparts)
# Submit `coroutine` on each worker given the df_parts that
# belong the specific worker as input
ret = []
for rank, worker in enumerate(comms.worker_addresses):
if rank in world:
dfs = []
for df_parts in df_parts_list:
dfs.append(df_parts.get(worker, []))
ret.append(
comms.submit(worker, coroutine, world, dfs_nparts, dfs, *extra_args)
)
wait(ret)
return dd.from_delayed(ret)
def merge(left, right, on=None, left_on=None, right_on=None):
"""Merge two DataFrames using explicit-comms.
This is an explicit-comms version of Dask's Dataframe.merge() that
only supports "inner" joins.
Requires an activate client.
Notice
------
As a side effect, this operation concatenate all partitions located on
the same worker thus npartitions of the returned dataframe equals number
of workers.
Parameters
----------
left: dask.dataframe.DataFrame
right: dask.dataframe.DataFrame
on : str or list of str
Column or index level names to join on. These must be found in both
DataFrames.
left_on : str or list of str
Column to join on in the left DataFrame.
right_on : str or list of str
Column to join on in the right DataFrame.
Returns
-------
df: dask.dataframe.DataFrame
Merged dataframe
"""
# Making sure that the "on" arguments are list of column names
if on:
on = [on] if isinstance(on, str) else list(on)
if left_on:
left_on = [left_on] if isinstance(left_on, str) else list(left_on)
if right_on:
right_on = [right_on] if isinstance(right_on, str) else list(right_on)
if left_on is None:
left_on = on
if right_on is None:
right_on = on
if not (left_on and right_on):
raise ValueError(
"Some combination of the on, left_on, and right_on arguments must be set"
)
return submit_dataframe_operation(
comms.default_comms(),
local_df_merge,
df_list=(left, right),
extra_args=(left_on, right_on),
) | en | 0.750216 | Making sure df_parts is a single dataframe or None Splits dataframe into partitions The partitions is determined by the hash value of the rows in `columns`. Parameters ---------- df: DataFrame columns: label or list Column names on which to split the dataframe npartition: int Number of partitions ignore_index : bool, default False Set True to ignore the index of `df` Returns ------- out: Dict[int, DataFrame] A dictionary mapping integers in {0..npartition} to dataframes. # Hashing `columns` in `df` and assign it to the "_partitions" column # Split `df` based on the hash values in the "_partitions" column # For Dask < 2.17 compatibility # Let's remove the partition column and return the partitions Worker job that merge local DataFrames Parameters ---------- s: dict Worker session state workers: set Set of ranks of all the participants dfs_nparts: list of dict List of dict that for each worker rank specifices the number of partitions that worker has. If the worker doesn't have any partitions, it is excluded from the dict. E.g. `dfs_nparts[0][1]` is how many partitions of the "left" dataframe worker 1 has. dfs_parts: list of lists of Dataframes List of inputs, which in this case are two dataframe lists. left_on : str or list of str Column to join on in the left DataFrame. right_on : str or list of str Column to join on in the right DataFrame. Returns ------- df: DataFrame Merged dataframe # Trimming such that all participanting workers get a rank within 0..len(workers) # Extracting the only key in `dfs_nparts[0]` # Extracting the only key in `dfs_nparts[1]` Returns the mapping: worker -> [list of futures] # Map worker -> [list of futures] # If multiple workers have the part, we pick the first worker Submit an operation on a list of Dask dataframe Parameters ---------- coroutine: coroutine The function to run on each worker. df_list: list of Dask.dataframe.Dataframe Input dataframes extra_args: tuple Extra function input Returns ------- dataframe: dask.dataframe.DataFrame The resulting dataframe # Let's create a dict for each dataframe that specifices the # number of partitions each worker has # Submit `coroutine` on each worker given the df_parts that # belong the specific worker as input Merge two DataFrames using explicit-comms. This is an explicit-comms version of Dask's Dataframe.merge() that only supports "inner" joins. Requires an activate client. Notice ------ As a side effect, this operation concatenate all partitions located on the same worker thus npartitions of the returned dataframe equals number of workers. Parameters ---------- left: dask.dataframe.DataFrame right: dask.dataframe.DataFrame on : str or list of str Column or index level names to join on. These must be found in both DataFrames. left_on : str or list of str Column to join on in the left DataFrame. right_on : str or list of str Column to join on in the right DataFrame. Returns ------- df: dask.dataframe.DataFrame Merged dataframe # Making sure that the "on" arguments are list of column names | 2.388116 | 2 |
Deep Count.py | fatih-iver-2016400264/Intro-to-Computer-Science-with-Python | 0 | 6620592 | <reponame>fatih-iver-2016400264/Intro-to-Computer-Science-with-Python<gh_stars>0
# Deep Count
# The built-in len operator outputs the number of top-level elements in a List,
# but not the total number of elements. For this question, your goal is to count
# the total number of elements in a list, including all of the inner lists.
# Define a procedure, deep_count, that takes as input a list, and outputs the
# total number of elements in the list, including all elements in lists that it
# contains.
# For this procedure, you will need a way to test if a value is a list. We have
# provided a procedure, is_list(p) that does this:
def is_list(p):
return isinstance(p, list)
# It is not necessary to understand how is_list works. It returns True if the
# input is a List, and returns False otherwise.
def deep_count(p):
total = 0
for elem in p:
if is_list(elem):
total += 1
total += deep_count(elem)
else:
total += 1
return total
print (deep_count([1, 2, 3]))
#>>> 3
# The empty list still counts as an element of the outer list
print (deep_count([1, [], 3]))
#>>> 3
print (deep_count([1, [1, 2, [3, 4]]]))
#>>> 7
print (deep_count([[[[[[[[1, 2, 3]]]]]]]]))
#>>> 10
| # Deep Count
# The built-in len operator outputs the number of top-level elements in a List,
# but not the total number of elements. For this question, your goal is to count
# the total number of elements in a list, including all of the inner lists.
# Define a procedure, deep_count, that takes as input a list, and outputs the
# total number of elements in the list, including all elements in lists that it
# contains.
# For this procedure, you will need a way to test if a value is a list. We have
# provided a procedure, is_list(p) that does this:
def is_list(p):
return isinstance(p, list)
# It is not necessary to understand how is_list works. It returns True if the
# input is a List, and returns False otherwise.
def deep_count(p):
total = 0
for elem in p:
if is_list(elem):
total += 1
total += deep_count(elem)
else:
total += 1
return total
print (deep_count([1, 2, 3]))
#>>> 3
# The empty list still counts as an element of the outer list
print (deep_count([1, [], 3]))
#>>> 3
print (deep_count([1, [1, 2, [3, 4]]]))
#>>> 7
print (deep_count([[[[[[[[1, 2, 3]]]]]]]]))
#>>> 10 | en | 0.878094 | # Deep Count # The built-in len operator outputs the number of top-level elements in a List, # but not the total number of elements. For this question, your goal is to count # the total number of elements in a list, including all of the inner lists. # Define a procedure, deep_count, that takes as input a list, and outputs the # total number of elements in the list, including all elements in lists that it # contains. # For this procedure, you will need a way to test if a value is a list. We have # provided a procedure, is_list(p) that does this: # It is not necessary to understand how is_list works. It returns True if the # input is a List, and returns False otherwise. #>>> 3 # The empty list still counts as an element of the outer list #>>> 3 #>>> 7 #>>> 10 | 4.380731 | 4 |
_solutions/pandas/import-export/pandas_readjson_a.py | sages-pl/2022-01-pythonsqlalchemy-aptiv | 0 | 6620593 | <reponame>sages-pl/2022-01-pythonsqlalchemy-aptiv
result = pd.read_json(DATA)
| result = pd.read_json(DATA) | none | 1 | 1.782552 | 2 | |
app/app/test.py | shashanksri99/recipe-app-api | 0 | 6620594 | from django.test import TestCase
from app.calc import add, substract
class CalcTest(TestCase):
def test_add_numbers(self):
"""
Test that two numbers are added together
"""
self.assertEqual(add(3, 8), 11)
def test_subtract_numbers(self):
"""
This will substract two numbers and return the result
"""
self.assertEqual(substract(8, 3), 5)
| from django.test import TestCase
from app.calc import add, substract
class CalcTest(TestCase):
def test_add_numbers(self):
"""
Test that two numbers are added together
"""
self.assertEqual(add(3, 8), 11)
def test_subtract_numbers(self):
"""
This will substract two numbers and return the result
"""
self.assertEqual(substract(8, 3), 5)
| en | 0.910617 | Test that two numbers are added together This will substract two numbers and return the result | 3.331411 | 3 |
30 Days of Code Challenges/Day 3: Intro to Conditional Statements.py | ArchieR7/HackerRank | 2 | 6620595 | <reponame>ArchieR7/HackerRank
import sys
N = int(input().strip())
if N % 2 == 1 or 6 <= N <= 20:
print("Weird")
else :
print("Not Weird")
| import sys
N = int(input().strip())
if N % 2 == 1 or 6 <= N <= 20:
print("Weird")
else :
print("Not Weird") | none | 1 | 3.645151 | 4 | |
src/repo.py | Jpfonseca/Blockchain_auction_management | 0 | 6620596 | import hashlib
import os, datetime, sys, json, base64, re, copy
import random
import string
from os import listdir
from ast import literal_eval
from socket import *
from blockchain import *
from logging import DEBUG, ERROR, INFO
from log import LoggyLogglyMcface
from security import *
from cc_interface import PortugueseCitizenCard
HOST = "127.0.0.1"
PORT_MAN = 8080
PORT_REPO = 8081
MAX_BUFFER_SIZE = 10000
class Repository():
def __init__(self, host, port):
LOG = "./log.txt"
for filename in listdir("./"):
if filename == "log.txt":
os.remove(LOG)
self.mylogger = LoggyLogglyMcface(name=Repository.__name__)
self.mylogger.log(INFO, "Entering Repository interface")
# repository information
self.name = Repository.__name__
self.privKname = "privK" + self.name
self.password = "<PASSWORD>"
self.repo_pubkey = None
self.man_pubkey = None
self.host = host
self.port = port
self.loggedInClient = 0
# client public keys
self.clients_pubkey = set()
# Addresses of clients and manager
self.address_client = []
self.manager_address = None
# list of active and closed auctions
self.active_auctions = []
self.closed_auctions = []
self.all_auctions = []
self.sock = socket(AF_INET, SOCK_DGRAM)
self.sock.bind((self.host, self.port))
# incremental serial number of the auctions
self.serial = 0
# hash of the previous block (auction serial, previous hash)
self.hash_prev = {}
# generate public and private key
self.certgen = GenerateCertificates()
self.certops = CertificateOperations()
self.crypto = CryptoUtils()
# dictionary of id of the client and public key
self.pubkey_dict = {}
# client is waiting for message (after sending proof-of-work result)
self.current_client = None
self.client_waiting = False
def start(self):
"""
Servers and Client exchange public keys
"""
try:
# verify if repository private key already exists. load if true
if self.certgen.checkExistence(self.name):
self.certgen.loadPrivateKeyFromFile(self.privKname, password=self.password)
else:
self.certgen.writePrivateKeyToFile(self.privKname, password=self.password)
self.repo_pubkey = self.certgen.publicKeyToBytes()
print("Listening...")
self.mylogger.log(INFO, "Exchanging public key with the manager")
data1, self.manager_address = self.sock.recvfrom(MAX_BUFFER_SIZE)
print("> manager pubkey received")
msg = json.dumps({'repo_pubk': self.repo_pubkey.decode()})
bytes = self.sock.sendto(msg.encode(), self.manager_address)
self.mylogger.log(INFO, "Manager public key received")
data1 = json.loads(data1)
if 'man_pubk' in data1:
self.man_pubkey = data1['man_pubk']
self.mylogger.log(INFO, "Man Pubkey : \n{}".format(self.man_pubkey))
self.mylogger.log(INFO, "Exchanging public key with the client")
data2, client_addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
print("> client pubkey received")
bytes = self.sock.sendto(msg.encode(), client_addr)
self.mylogger.log(INFO, "Client public key received")
data2 = json.loads(data2)
self.client_login(data2, client_addr)
self.loop()
except:
self.mylogger.log(INFO, "Cannot start repository")
raise
def loop(self):
"""
The main loop of the repository. It waits for messages of clients
(both system clients or servers) and calls functions according
to the received messages
"""
try:
while (True):
date_time = datetime.datetime.now()
for auction in self.active_auctions:
timestamp_auction = datetime.datetime.strptime(auction.timestamp, '%m/%d/%Y, %H:%M:%S')
delta = date_time - timestamp_auction
seconds = delta.days * 24 * 3600 + delta.seconds
time_limit = re.findall('\d+', auction.time_limit)
time_limit = (int(time_limit[0]) * 3600) + (int(time_limit[1]) * 60) + int(time_limit[2])
print("info: {} seconds have passed on auction {}".format(seconds, auction.serial))
if seconds > time_limit:
print("> auction {} has ended".format(auction.serial))
self.closed_auctions.append(auction)
self.active_auctions.remove(auction)
file = "auction{}.txt".format(auction.serial)
current_path = os.getcwd()
path = "{}/auctions/{}".format(current_path, file)
msg = {'payload': {'end': path}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.manager_address)
data, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data = json.loads(data)
signature = base64.b64decode(data['signature'])
if self.valid_signature(self.man_pubkey, json.dumps(data['payload']), signature):
if data['payload']['ack'] == 'ok':
with open(path) as f:
lines = f.readlines()
lines = [x.strip("\n") for x in lines]
blockchain = None
for i in range(len(lines)):
lines_dict = literal_eval(lines[i])
if i == 0:
current_serial = lines_dict['serial']
blockchain = Blockchain(lines_dict['key'], lines_dict['cert'], lines_dict['serial'],
lines_dict['id'], lines_dict['timestamp'],
lines_dict['name'], lines_dict['time-limit'],
lines_dict['description'], lines_dict['type'],
lines_dict['state'], lines_dict['winner'],
lines_dict['winner_amount'])
else:
block = Block(lines_dict['key'], lines_dict['cert'], lines_dict['serial'],
lines_dict['hash'], lines_dict['hash_prev'], lines_dict['amount'],
lines_dict['name'], lines_dict['id'], lines_dict['timestamp'])
blockchain.add_block(block)
for a in range(len(self.closed_auctions)):
if auction.serial == self.closed_auctions[a].serial:
self.closed_auctions[a] = blockchain
for a in range(len(self.all_auctions)):
if auction.serial == self.all_auctions[a].serial:
self.all_auctions[a] = blockchain
if self.client_waiting:
msg = {'payload': {'ack': 'nok', 'info': 'busy: bid no created'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.current_client)
else:
print("> no bids on ended auction {} -> no possible winner".format(auction.serial))
else:
print("> couldn't find the winner")
data, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data = json.loads(data)
if (addr not in self.address_client) and (addr != self.manager_address):
print("> client pubkey received")
msg = json.dumps({'repo_pubk': self.repo_pubkey.decode()})
bytes = self.sock.sendto(msg.encode(), addr)
self.client_login(data, addr)
else:
self.client_waiting = False
if 'auction' in data['payload']:
signature = base64.b64decode(data['signature'])
if data['payload']['valid']:
if self.valid_signature(self.man_pubkey, json.dumps(data['payload']), signature):
data2 = data['payload']
self.create_auction(addr, data2['auction']['key'], data2['auction']['cert'],
self.serial + 1, data2['auction']['id'], data2['auction']['timestamp'],
data2['auction']['name'], data2['auction']['time-limit'],
data2['auction']['description'], data2['auction']['type'])
elif 'bid' in data['payload']:
data2 = copy.deepcopy(data)
signature = base64.b64decode(data2['payload'].pop('sig_c'))
if self.crypto.verifySignatureCC(self.pubkey_dict[data['payload']['bid']['id']], json.dumps(data2['payload']), signature):
self.place_bid(addr, data['payload'])
elif 'command' in data['payload']:
signature = base64.b64decode(data['signature'])
data2 = data['payload']
payload = json.dumps(data2)
if 'bid_request' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.send_pow(addr, data2)
elif 'list_open' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_open(addr)
elif 'list_closed' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_closed(addr)
elif 'bid_auction' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.bids_auction(addr, data2['serial'])
elif 'bid_client' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.bids_client(addr, data2['c_id'])
elif 'check_receipt' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.check_receipt(addr, data2['serial'], data2['hash'])
elif 'list_ids' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_ids(addr)
if 'exit' in data['payload']:
msg = json.dumps({'payload': {'exit': 'client exit'}})
signature = base64.b64decode(data['signature'])
if self.crypto.verifySignatureCC(self.pubkey_dict[data['payload']['id']], json.dumps(data['payload']), signature):
self.loggedInClient -= 1
if self.loggedInClient <= 0:
self.mylogger.log(INFO, "Exiting Repository")
self.exit(0)
for auction in self.active_auctions:
file = "auction{}.txt".format(auction.serial)
auction.save_to_file(file)
except:
self.mylogger.log(INFO, "Exception on repository server's loop ")
raise
def create_auction(self, addr, key, cert, serial, id, timestamp, name, timelimit, description, type):
"""
Create an auction (new blockchain) and store it in a file
after receiving its parameters from the manager server
"""
try:
self.mylogger.log(INFO, "Create auction ")
blockchain = Blockchain(key, cert, serial, id, timestamp, name, timelimit, description, type, state='active')
self.serial = self.serial + 1
print("> auction creation: OK")
self.active_auctions.append(blockchain)
self.all_auctions.append(blockchain)
self.hash_prev[str(serial)] = '0'
msg = {'payload': {'ack': 'ok', 'info': 'auction', 'id': id, 'serial': str(serial)}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), addr)
except:
self.mylogger.log(INFO, "Auction cannot be created ")
print("> auction creation: NOT OK\n")
msg = {'payload': {'ack': 'nok', 'info': 'auction', 'id': id}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), addr)
# send the proof-of-work to client. The cryptopuzzle is a hash-cash
def send_pow(self, address_client, data):
"""
Send proof-of-work to the client (random string and number of zeros required).
A response with a string and a digest is received and the function calculates
the SHA256 digest of the string and compares it with the digest, also sent by the client.
If equal, the client may send the bid parameters.
"""
try:
self.mylogger.log(INFO, "Sending proof-of-work to client ")
type = ""
auction_exists = False
for auction in self.active_auctions:
if str(auction.serial) == data['serial']:
type = auction.type
auction_exists = True
if auction_exists is False:
msg = {'payload': {'ack': 'nok', 'info': 'auction does not exist'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
else:
r_string = ''.join(
random.choice(string.digits + string.ascii_lowercase + string.ascii_uppercase) for c in range(6))
msg = {'payload': {'ack': 'ok', 'r_string': r_string, 'numZeros': '5', 'type': type,
'hash_prev': self.hash_prev[data['serial']]}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
data2, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data2 = json.loads(data2)
signature = base64.b64decode(data2['signature'])
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['payload']['id']],
json.dumps(data2['payload']), signature):
if 'digest' in data2['payload']:
print("> proof-of-work result of client: " + json.dumps(data2['payload']['digest']))
hash_object = hashlib.sha256(data2['payload']['string'].encode('utf-8'))
digest = hash_object.hexdigest()
if data2['payload']['digest'] == digest:
msg2 = {'payload': {'ack': 'ok', 'type': type, 'hash_prev': self.hash_prev[data['serial']]}}
self.current_client = addr
self.client_waiting = True
else:
msg2 = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg2['payload']))).decode()
msg2['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg2).encode(), address_client)
else:
msg2 = {'payload': {'ack': 'nok', 'info': 'busy: could not send proof-of-work'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg2['payload']))).decode()
msg2['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg2).encode(), address_client)
except:
print("Cannot send proof-of-work to client")
self.mylogger.log(INFO, "Cannot send proof-of-work to client ")
raise
def place_bid(self, addr, data):
"""
Receives the new bid parameters, creates a new block and
inserts it in the blockchain of the respective auction
"""
try:
self.mylogger.log(INFO, "Place a bid ")
client_address = addr
for auction in self.active_auctions:
if data['bid']['serial'] == str(auction.serial):
block = Block(data['bid']['key'], data['bid']['cert'], data['bid']['serial'], data['bid']['hash'],
data['bid']['hash_prev'], data['bid']['amount'], data['bid']['name'],
data['bid']['id'], data['bid']['timestamp'])
self.hash_prev[data['bid']['serial']] = data['bid']['hash']
msg = {'payload': {'bid_valid': data}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.manager_address)
data2, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data2 = json.loads(data2)
signature = base64.b64decode(data2['signature'])
payload = json.dumps(data2['payload'])
if self.valid_signature(self.man_pubkey, payload, signature):
if data2['payload']['valid'] is True:
auction.add_block(block)
print("> bid creation in auction {}: OK".format(auction.serial))
signature = base64.b64encode(self.certgen.signData(json.dumps(data2['payload']['receipt']))).decode()
data2['payload']['receipt']['sig_r'] = signature
msg = {'payload': {'ack': 'ok', 'receipt': data2['payload']['receipt']}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
break
else:
print("> bid creation in auction {}: NOK".format(auction.serial))
if 'info' in data2['payload']:
msg = {'payload': {'ack': 'nok', 'info': data2['payload']['info']}}
else:
msg = {'payload': {'ack': 'nok', 'valid': data2['payload']['valid']}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
break
else:
print("> bid creation in auction {}: NOK".format(auction.serial))
msg = {'payload': {'ack': 'nok', 'info': 'non active'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
except:
print("Cannot create bid")
self.mylogger.log(INFO, "Cannot create bid ")
raise
def list_ids(self, address_client):
"""
Send list of the IDs of the clients of the system
"""
try:
self.mylogger.log(INFO, "Listing active auctions")
if self.pubkey_dict:
msg = {'payload': {'ack': 'ok', 'ids': list(self.pubkey_dict.keys())}}
else:
msg = msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
self.mylogger.log(INFO, "Cannot list ids of clients")
raise
def list_open(self, address_client):
"""
Send list of the currently active auctions
"""
try:
self.mylogger.log(INFO, "Listing active auctions")
auctions = ""
for auction in self.active_auctions:
auctions = auctions + str(auction.info_user()) + "\n"
if auctions != "":
msg = {'payload': auctions}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("> sending list of active auctions")
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("Cannot send active auctions")
self.mylogger.log(INFO, "Cannot send active auctions ")
raise
def list_closed(self, address_client):
"""
Send list of the closed auctions
"""
try:
self.mylogger.log(INFO, "Listing closed auctions ")
auctions = ""
for auction in self.closed_auctions:
auctions = auctions + str(auction.info_user()) + "\n"
if auctions != "":
msg = {'payload': auctions}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("> sending list of closed auctions")
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("Can't send active auctions")
self.mylogger.log(INFO, "Cannot send active auctions ")
raise
def bids_auction(self, address_client, serial):
"""
Send list of all the bids of an auction
"""
try:
self.mylogger.log(INFO, "Listing bids of auction {} ".format(serial))
msg = {}
i = 0
result = None
auctions_exists = False
for auction in self.all_auctions:
if auction.serial == int(serial):
auctions_exists = True
result = auction.bids_auction(serial)
if auctions_exists:
for bid in result:
bid_number = "bid_{}".format(i)
msg[bid_number] = bid
i = i + 1
msg = {'payload': msg}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("\n> sent list of bids of auction {}".format(serial))
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> cannot send list of bids of auction {}".format(serial))
self.mylogger.log(INFO, "Cannot list bids of auction {}".format(serial))
raise
def bids_client(self, address_client, id):
"""
Send list of all the bids of a client
"""
try:
self.mylogger.log(INFO, "Listing bids of client {} ".format(id))
msg = {}
i = 0
result = None
client_exists = False
for auction in self.all_auctions:
if str(auction.id) == id:
client_exists = True
result = auction.bids_client(id)
if client_exists:
for bid in result:
bid_number = "bid_{}".format(i)
msg[bid_number] = bid
i = i + 1
msg = {'payload': msg}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("\n> sent list of bids of client {}".format(id))
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> can't send list of bids of client {}".format(id))
self.mylogger.log(INFO, "Listing bids of client {} ".format(id))
raise
def check_receipt(self, address_client, serial, hash):
"""
Send bid information to a client requesting it, for
validation against a receipt.
"""
try:
self.mylogger.log(INFO, "Sending bid information for receipt validation ")
print("> sending bid information for receipt validation")
closed_auctions = False
for auction in self.closed_auctions:
if str(auction.serial) == serial:
closed_auctions = True
info = auction.bid_info(hash)
if info != "":
msg = {'payload': {'bid': info}}
else:
msg = {'payload': {'ack': 'nok', 'info': 'no info about bid'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
else:
msg = {'payload': {'ack': 'nok', 'info': 'the auction is not closed'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
if not closed_auctions:
msg = {'payload': {'ack': 'nok', 'info': 'no closed auctions'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> cannot send bid information for receipt validation")
self.mylogger.log(INFO, "Cannot send bid information for receipt validation ")
def client_login(self, message, client_addr):
"""
Storing information on a new client of the system
"""
try:
self.mylogger.log(INFO, "Adding new client ")
cert = None
if 'c_pubk' in message:
self.mylogger.log(INFO, "Client Pubkey : \n{}".format(message['c_pubk']))
self.loggedInClient += 1
self.pubkey_dict[message['id']] = message['c_pubk']
self.address_client.append(client_addr)
except:
print("Cannot sign up new client")
self.mylogger.log(INFO, "Cannot signup new client ")
raise
def valid_signature(self, pubk, message, signature):
"""
Validate an entity's signature on a message
"""
try:
pubk = self.crypto.loadPubk(pubk)
if not self.crypto.verifySignatureServers(pubk, message, signature):
return False
return True
except:
print("Cannot validate signature")
self.mylogger.log(INFO, "Cannot validate signature ")
raise
def exit(self, type):
"""
Shutdown the repository
"""
try:
self.mylogger.log(INFO, "Exiting repository ")
print("Exiting...")
self.sock.close()
sys.exit(type)
except:
self.mylogger.log(INFO, "Cannot exit repository ")
raise
if __name__ == "__main__":
r = Repository(HOST, PORT_REPO)
try:
r.start()
except KeyboardInterrupt:
print("Exiting...")
| import hashlib
import os, datetime, sys, json, base64, re, copy
import random
import string
from os import listdir
from ast import literal_eval
from socket import *
from blockchain import *
from logging import DEBUG, ERROR, INFO
from log import LoggyLogglyMcface
from security import *
from cc_interface import PortugueseCitizenCard
HOST = "127.0.0.1"
PORT_MAN = 8080
PORT_REPO = 8081
MAX_BUFFER_SIZE = 10000
class Repository():
def __init__(self, host, port):
LOG = "./log.txt"
for filename in listdir("./"):
if filename == "log.txt":
os.remove(LOG)
self.mylogger = LoggyLogglyMcface(name=Repository.__name__)
self.mylogger.log(INFO, "Entering Repository interface")
# repository information
self.name = Repository.__name__
self.privKname = "privK" + self.name
self.password = "<PASSWORD>"
self.repo_pubkey = None
self.man_pubkey = None
self.host = host
self.port = port
self.loggedInClient = 0
# client public keys
self.clients_pubkey = set()
# Addresses of clients and manager
self.address_client = []
self.manager_address = None
# list of active and closed auctions
self.active_auctions = []
self.closed_auctions = []
self.all_auctions = []
self.sock = socket(AF_INET, SOCK_DGRAM)
self.sock.bind((self.host, self.port))
# incremental serial number of the auctions
self.serial = 0
# hash of the previous block (auction serial, previous hash)
self.hash_prev = {}
# generate public and private key
self.certgen = GenerateCertificates()
self.certops = CertificateOperations()
self.crypto = CryptoUtils()
# dictionary of id of the client and public key
self.pubkey_dict = {}
# client is waiting for message (after sending proof-of-work result)
self.current_client = None
self.client_waiting = False
def start(self):
"""
Servers and Client exchange public keys
"""
try:
# verify if repository private key already exists. load if true
if self.certgen.checkExistence(self.name):
self.certgen.loadPrivateKeyFromFile(self.privKname, password=self.password)
else:
self.certgen.writePrivateKeyToFile(self.privKname, password=self.password)
self.repo_pubkey = self.certgen.publicKeyToBytes()
print("Listening...")
self.mylogger.log(INFO, "Exchanging public key with the manager")
data1, self.manager_address = self.sock.recvfrom(MAX_BUFFER_SIZE)
print("> manager pubkey received")
msg = json.dumps({'repo_pubk': self.repo_pubkey.decode()})
bytes = self.sock.sendto(msg.encode(), self.manager_address)
self.mylogger.log(INFO, "Manager public key received")
data1 = json.loads(data1)
if 'man_pubk' in data1:
self.man_pubkey = data1['man_pubk']
self.mylogger.log(INFO, "Man Pubkey : \n{}".format(self.man_pubkey))
self.mylogger.log(INFO, "Exchanging public key with the client")
data2, client_addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
print("> client pubkey received")
bytes = self.sock.sendto(msg.encode(), client_addr)
self.mylogger.log(INFO, "Client public key received")
data2 = json.loads(data2)
self.client_login(data2, client_addr)
self.loop()
except:
self.mylogger.log(INFO, "Cannot start repository")
raise
def loop(self):
"""
The main loop of the repository. It waits for messages of clients
(both system clients or servers) and calls functions according
to the received messages
"""
try:
while (True):
date_time = datetime.datetime.now()
for auction in self.active_auctions:
timestamp_auction = datetime.datetime.strptime(auction.timestamp, '%m/%d/%Y, %H:%M:%S')
delta = date_time - timestamp_auction
seconds = delta.days * 24 * 3600 + delta.seconds
time_limit = re.findall('\d+', auction.time_limit)
time_limit = (int(time_limit[0]) * 3600) + (int(time_limit[1]) * 60) + int(time_limit[2])
print("info: {} seconds have passed on auction {}".format(seconds, auction.serial))
if seconds > time_limit:
print("> auction {} has ended".format(auction.serial))
self.closed_auctions.append(auction)
self.active_auctions.remove(auction)
file = "auction{}.txt".format(auction.serial)
current_path = os.getcwd()
path = "{}/auctions/{}".format(current_path, file)
msg = {'payload': {'end': path}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.manager_address)
data, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data = json.loads(data)
signature = base64.b64decode(data['signature'])
if self.valid_signature(self.man_pubkey, json.dumps(data['payload']), signature):
if data['payload']['ack'] == 'ok':
with open(path) as f:
lines = f.readlines()
lines = [x.strip("\n") for x in lines]
blockchain = None
for i in range(len(lines)):
lines_dict = literal_eval(lines[i])
if i == 0:
current_serial = lines_dict['serial']
blockchain = Blockchain(lines_dict['key'], lines_dict['cert'], lines_dict['serial'],
lines_dict['id'], lines_dict['timestamp'],
lines_dict['name'], lines_dict['time-limit'],
lines_dict['description'], lines_dict['type'],
lines_dict['state'], lines_dict['winner'],
lines_dict['winner_amount'])
else:
block = Block(lines_dict['key'], lines_dict['cert'], lines_dict['serial'],
lines_dict['hash'], lines_dict['hash_prev'], lines_dict['amount'],
lines_dict['name'], lines_dict['id'], lines_dict['timestamp'])
blockchain.add_block(block)
for a in range(len(self.closed_auctions)):
if auction.serial == self.closed_auctions[a].serial:
self.closed_auctions[a] = blockchain
for a in range(len(self.all_auctions)):
if auction.serial == self.all_auctions[a].serial:
self.all_auctions[a] = blockchain
if self.client_waiting:
msg = {'payload': {'ack': 'nok', 'info': 'busy: bid no created'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.current_client)
else:
print("> no bids on ended auction {} -> no possible winner".format(auction.serial))
else:
print("> couldn't find the winner")
data, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data = json.loads(data)
if (addr not in self.address_client) and (addr != self.manager_address):
print("> client pubkey received")
msg = json.dumps({'repo_pubk': self.repo_pubkey.decode()})
bytes = self.sock.sendto(msg.encode(), addr)
self.client_login(data, addr)
else:
self.client_waiting = False
if 'auction' in data['payload']:
signature = base64.b64decode(data['signature'])
if data['payload']['valid']:
if self.valid_signature(self.man_pubkey, json.dumps(data['payload']), signature):
data2 = data['payload']
self.create_auction(addr, data2['auction']['key'], data2['auction']['cert'],
self.serial + 1, data2['auction']['id'], data2['auction']['timestamp'],
data2['auction']['name'], data2['auction']['time-limit'],
data2['auction']['description'], data2['auction']['type'])
elif 'bid' in data['payload']:
data2 = copy.deepcopy(data)
signature = base64.b64decode(data2['payload'].pop('sig_c'))
if self.crypto.verifySignatureCC(self.pubkey_dict[data['payload']['bid']['id']], json.dumps(data2['payload']), signature):
self.place_bid(addr, data['payload'])
elif 'command' in data['payload']:
signature = base64.b64decode(data['signature'])
data2 = data['payload']
payload = json.dumps(data2)
if 'bid_request' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.send_pow(addr, data2)
elif 'list_open' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_open(addr)
elif 'list_closed' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_closed(addr)
elif 'bid_auction' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.bids_auction(addr, data2['serial'])
elif 'bid_client' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.bids_client(addr, data2['c_id'])
elif 'check_receipt' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.check_receipt(addr, data2['serial'], data2['hash'])
elif 'list_ids' in data2['command']:
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['id']], payload, signature):
self.list_ids(addr)
if 'exit' in data['payload']:
msg = json.dumps({'payload': {'exit': 'client exit'}})
signature = base64.b64decode(data['signature'])
if self.crypto.verifySignatureCC(self.pubkey_dict[data['payload']['id']], json.dumps(data['payload']), signature):
self.loggedInClient -= 1
if self.loggedInClient <= 0:
self.mylogger.log(INFO, "Exiting Repository")
self.exit(0)
for auction in self.active_auctions:
file = "auction{}.txt".format(auction.serial)
auction.save_to_file(file)
except:
self.mylogger.log(INFO, "Exception on repository server's loop ")
raise
def create_auction(self, addr, key, cert, serial, id, timestamp, name, timelimit, description, type):
"""
Create an auction (new blockchain) and store it in a file
after receiving its parameters from the manager server
"""
try:
self.mylogger.log(INFO, "Create auction ")
blockchain = Blockchain(key, cert, serial, id, timestamp, name, timelimit, description, type, state='active')
self.serial = self.serial + 1
print("> auction creation: OK")
self.active_auctions.append(blockchain)
self.all_auctions.append(blockchain)
self.hash_prev[str(serial)] = '0'
msg = {'payload': {'ack': 'ok', 'info': 'auction', 'id': id, 'serial': str(serial)}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), addr)
except:
self.mylogger.log(INFO, "Auction cannot be created ")
print("> auction creation: NOT OK\n")
msg = {'payload': {'ack': 'nok', 'info': 'auction', 'id': id}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), addr)
# send the proof-of-work to client. The cryptopuzzle is a hash-cash
def send_pow(self, address_client, data):
"""
Send proof-of-work to the client (random string and number of zeros required).
A response with a string and a digest is received and the function calculates
the SHA256 digest of the string and compares it with the digest, also sent by the client.
If equal, the client may send the bid parameters.
"""
try:
self.mylogger.log(INFO, "Sending proof-of-work to client ")
type = ""
auction_exists = False
for auction in self.active_auctions:
if str(auction.serial) == data['serial']:
type = auction.type
auction_exists = True
if auction_exists is False:
msg = {'payload': {'ack': 'nok', 'info': 'auction does not exist'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
else:
r_string = ''.join(
random.choice(string.digits + string.ascii_lowercase + string.ascii_uppercase) for c in range(6))
msg = {'payload': {'ack': 'ok', 'r_string': r_string, 'numZeros': '5', 'type': type,
'hash_prev': self.hash_prev[data['serial']]}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
data2, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data2 = json.loads(data2)
signature = base64.b64decode(data2['signature'])
if self.crypto.verifySignatureCC(self.pubkey_dict[data2['payload']['id']],
json.dumps(data2['payload']), signature):
if 'digest' in data2['payload']:
print("> proof-of-work result of client: " + json.dumps(data2['payload']['digest']))
hash_object = hashlib.sha256(data2['payload']['string'].encode('utf-8'))
digest = hash_object.hexdigest()
if data2['payload']['digest'] == digest:
msg2 = {'payload': {'ack': 'ok', 'type': type, 'hash_prev': self.hash_prev[data['serial']]}}
self.current_client = addr
self.client_waiting = True
else:
msg2 = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg2['payload']))).decode()
msg2['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg2).encode(), address_client)
else:
msg2 = {'payload': {'ack': 'nok', 'info': 'busy: could not send proof-of-work'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg2['payload']))).decode()
msg2['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg2).encode(), address_client)
except:
print("Cannot send proof-of-work to client")
self.mylogger.log(INFO, "Cannot send proof-of-work to client ")
raise
def place_bid(self, addr, data):
"""
Receives the new bid parameters, creates a new block and
inserts it in the blockchain of the respective auction
"""
try:
self.mylogger.log(INFO, "Place a bid ")
client_address = addr
for auction in self.active_auctions:
if data['bid']['serial'] == str(auction.serial):
block = Block(data['bid']['key'], data['bid']['cert'], data['bid']['serial'], data['bid']['hash'],
data['bid']['hash_prev'], data['bid']['amount'], data['bid']['name'],
data['bid']['id'], data['bid']['timestamp'])
self.hash_prev[data['bid']['serial']] = data['bid']['hash']
msg = {'payload': {'bid_valid': data}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), self.manager_address)
data2, addr = self.sock.recvfrom(MAX_BUFFER_SIZE)
data2 = json.loads(data2)
signature = base64.b64decode(data2['signature'])
payload = json.dumps(data2['payload'])
if self.valid_signature(self.man_pubkey, payload, signature):
if data2['payload']['valid'] is True:
auction.add_block(block)
print("> bid creation in auction {}: OK".format(auction.serial))
signature = base64.b64encode(self.certgen.signData(json.dumps(data2['payload']['receipt']))).decode()
data2['payload']['receipt']['sig_r'] = signature
msg = {'payload': {'ack': 'ok', 'receipt': data2['payload']['receipt']}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
break
else:
print("> bid creation in auction {}: NOK".format(auction.serial))
if 'info' in data2['payload']:
msg = {'payload': {'ack': 'nok', 'info': data2['payload']['info']}}
else:
msg = {'payload': {'ack': 'nok', 'valid': data2['payload']['valid']}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
break
else:
print("> bid creation in auction {}: NOK".format(auction.serial))
msg = {'payload': {'ack': 'nok', 'info': 'non active'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), client_address)
except:
print("Cannot create bid")
self.mylogger.log(INFO, "Cannot create bid ")
raise
def list_ids(self, address_client):
"""
Send list of the IDs of the clients of the system
"""
try:
self.mylogger.log(INFO, "Listing active auctions")
if self.pubkey_dict:
msg = {'payload': {'ack': 'ok', 'ids': list(self.pubkey_dict.keys())}}
else:
msg = msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
self.mylogger.log(INFO, "Cannot list ids of clients")
raise
def list_open(self, address_client):
"""
Send list of the currently active auctions
"""
try:
self.mylogger.log(INFO, "Listing active auctions")
auctions = ""
for auction in self.active_auctions:
auctions = auctions + str(auction.info_user()) + "\n"
if auctions != "":
msg = {'payload': auctions}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("> sending list of active auctions")
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("Cannot send active auctions")
self.mylogger.log(INFO, "Cannot send active auctions ")
raise
def list_closed(self, address_client):
"""
Send list of the closed auctions
"""
try:
self.mylogger.log(INFO, "Listing closed auctions ")
auctions = ""
for auction in self.closed_auctions:
auctions = auctions + str(auction.info_user()) + "\n"
if auctions != "":
msg = {'payload': auctions}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("> sending list of closed auctions")
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("Can't send active auctions")
self.mylogger.log(INFO, "Cannot send active auctions ")
raise
def bids_auction(self, address_client, serial):
"""
Send list of all the bids of an auction
"""
try:
self.mylogger.log(INFO, "Listing bids of auction {} ".format(serial))
msg = {}
i = 0
result = None
auctions_exists = False
for auction in self.all_auctions:
if auction.serial == int(serial):
auctions_exists = True
result = auction.bids_auction(serial)
if auctions_exists:
for bid in result:
bid_number = "bid_{}".format(i)
msg[bid_number] = bid
i = i + 1
msg = {'payload': msg}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("\n> sent list of bids of auction {}".format(serial))
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> cannot send list of bids of auction {}".format(serial))
self.mylogger.log(INFO, "Cannot list bids of auction {}".format(serial))
raise
def bids_client(self, address_client, id):
"""
Send list of all the bids of a client
"""
try:
self.mylogger.log(INFO, "Listing bids of client {} ".format(id))
msg = {}
i = 0
result = None
client_exists = False
for auction in self.all_auctions:
if str(auction.id) == id:
client_exists = True
result = auction.bids_client(id)
if client_exists:
for bid in result:
bid_number = "bid_{}".format(i)
msg[bid_number] = bid
i = i + 1
msg = {'payload': msg}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
print("\n> sent list of bids of client {}".format(id))
else:
msg = {'payload': {'ack': 'nok'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> can't send list of bids of client {}".format(id))
self.mylogger.log(INFO, "Listing bids of client {} ".format(id))
raise
def check_receipt(self, address_client, serial, hash):
"""
Send bid information to a client requesting it, for
validation against a receipt.
"""
try:
self.mylogger.log(INFO, "Sending bid information for receipt validation ")
print("> sending bid information for receipt validation")
closed_auctions = False
for auction in self.closed_auctions:
if str(auction.serial) == serial:
closed_auctions = True
info = auction.bid_info(hash)
if info != "":
msg = {'payload': {'bid': info}}
else:
msg = {'payload': {'ack': 'nok', 'info': 'no info about bid'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
else:
msg = {'payload': {'ack': 'nok', 'info': 'the auction is not closed'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
if not closed_auctions:
msg = {'payload': {'ack': 'nok', 'info': 'no closed auctions'}}
signature = base64.b64encode(self.certgen.signData(json.dumps(msg['payload']))).decode()
msg['signature'] = signature
bytes = self.sock.sendto(json.dumps(msg).encode(), address_client)
except:
print("> cannot send bid information for receipt validation")
self.mylogger.log(INFO, "Cannot send bid information for receipt validation ")
def client_login(self, message, client_addr):
"""
Storing information on a new client of the system
"""
try:
self.mylogger.log(INFO, "Adding new client ")
cert = None
if 'c_pubk' in message:
self.mylogger.log(INFO, "Client Pubkey : \n{}".format(message['c_pubk']))
self.loggedInClient += 1
self.pubkey_dict[message['id']] = message['c_pubk']
self.address_client.append(client_addr)
except:
print("Cannot sign up new client")
self.mylogger.log(INFO, "Cannot signup new client ")
raise
def valid_signature(self, pubk, message, signature):
"""
Validate an entity's signature on a message
"""
try:
pubk = self.crypto.loadPubk(pubk)
if not self.crypto.verifySignatureServers(pubk, message, signature):
return False
return True
except:
print("Cannot validate signature")
self.mylogger.log(INFO, "Cannot validate signature ")
raise
def exit(self, type):
"""
Shutdown the repository
"""
try:
self.mylogger.log(INFO, "Exiting repository ")
print("Exiting...")
self.sock.close()
sys.exit(type)
except:
self.mylogger.log(INFO, "Cannot exit repository ")
raise
if __name__ == "__main__":
r = Repository(HOST, PORT_REPO)
try:
r.start()
except KeyboardInterrupt:
print("Exiting...")
| en | 0.883986 | # repository information # client public keys # Addresses of clients and manager # list of active and closed auctions # incremental serial number of the auctions # hash of the previous block (auction serial, previous hash) # generate public and private key # dictionary of id of the client and public key # client is waiting for message (after sending proof-of-work result) Servers and Client exchange public keys # verify if repository private key already exists. load if true The main loop of the repository. It waits for messages of clients (both system clients or servers) and calls functions according to the received messages Create an auction (new blockchain) and store it in a file after receiving its parameters from the manager server # send the proof-of-work to client. The cryptopuzzle is a hash-cash Send proof-of-work to the client (random string and number of zeros required). A response with a string and a digest is received and the function calculates the SHA256 digest of the string and compares it with the digest, also sent by the client. If equal, the client may send the bid parameters. Receives the new bid parameters, creates a new block and inserts it in the blockchain of the respective auction Send list of the IDs of the clients of the system Send list of the currently active auctions Send list of the closed auctions Send list of all the bids of an auction Send list of all the bids of a client Send bid information to a client requesting it, for validation against a receipt. Storing information on a new client of the system Validate an entity's signature on a message Shutdown the repository | 2.364812 | 2 |
python/packages/nisar/workflows/split_spectrum.py | isce3-testing/isce3-circleci-poc | 0 | 6620597 | #!/usr/bin/env python3
import os
import pathlib
import time
import h5py
import isce3
import journal
import numpy as np
from isce3.splitspectrum import splitspectrum
from nisar.h5 import cp_h5_meta_data
from nisar.products.readers import SLC
from nisar.workflows.split_spectrum_runconfig import SplitSpectrumRunConfig
from nisar.workflows.yaml_argparse import YamlArgparse
def prep_subband_h5(full_hdf5: str,
sub_band_hdf5: str,
freq_pols):
common_parent_path = 'science/LSAR'
swath_path = f'{common_parent_path}/SLC/swaths/'
freq_a_path = f'{swath_path}/frequencyA/'
freq_b_path = f'{swath_path}/frequencyB/'
metadata_path = f'{common_parent_path}/SLC/metadata/'
ident_path = f'{common_parent_path}/identification/'
pol_a_path = f'{freq_a_path}/listOfPolarizations'
pol_b_path = f'{freq_b_path}/listOfPolarizations'
with h5py.File(full_hdf5, 'r', libver='latest', swmr=True) as src_h5, \
h5py.File(sub_band_hdf5, 'w') as dst_h5:
pols_freqA = list(
np.array(src_h5[pol_a_path][()], dtype=str))
pols_freqB = list(
np.array(src_h5[pol_b_path][()], dtype=str))
if freq_pols['A']:
pols_a_excludes = [pol for pol in pols_freqA
if pol not in freq_pols['A']]
else:
pols_a_excludes = pols_freqA
if freq_pols['B']:
pols_b_excludes = [pol for pol in pols_freqB
if pol not in freq_pols['B']]
else:
pols_b_excludes = pols_freqB
if pols_a_excludes:
cp_h5_meta_data(src_h5, dst_h5, freq_a_path,
excludes=pols_a_excludes)
else:
cp_h5_meta_data(src_h5, dst_h5, freq_a_path,
excludes=[''])
if pols_b_excludes:
cp_h5_meta_data(src_h5, dst_h5, freq_b_path,
excludes=pols_b_excludes)
else:
cp_h5_meta_data(src_h5, dst_h5, freq_b_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, metadata_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, ident_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, swath_path,
excludes=['frequencyA', 'frequencyB'])
def run(cfg: dict):
'''
run bandpass
'''
# pull parameters from cfg
ref_hdf5 = cfg['input_file_group']['reference_rslc_file_path']
sec_hdf5 = cfg['input_file_group']['secondary_rslc_file_path']
# Extract range split spectrum dictionary and corresponding parameters
ionosphere_option = cfg['processing']['ionosphere_phase_correction']
method = ionosphere_option['spectral_diversity']
split_cfg = ionosphere_option['split_range_spectrum']
iono_freq_pol = ionosphere_option['list_of_frequencies']
blocksize = split_cfg['lines_per_block']
window_function = split_cfg['window_function']
window_shape = split_cfg['window_shape']
low_band_bandwidth = split_cfg['low_band_bandwidth']
high_band_bandwidth = split_cfg['high_band_bandwidth']
scratch_path = pathlib.Path(cfg['product_path_group']['scratch_path'])
info_channel = journal.info("split_spectrum.run")
info_channel.log("starting split_spectrum")
t_all = time.time()
# Check split spectrum method
if method == 'split_main_band':
split_band_path = pathlib.Path(
f"{scratch_path}/ionosphere/split_spectrum/")
split_band_path.mkdir(parents=True, exist_ok=True)
common_parent_path = 'science/LSAR'
freq = 'A'
pol_list = iono_freq_pol[freq]
info_channel.log(f'Split the main band {pol_list} of the signal')
for hdf5_ind, hdf5_str in enumerate([ref_hdf5, sec_hdf5]):
# reference SLC
if hdf5_ind == 0:
low_band_output = f"{split_band_path}/ref_low_band_slc.h5"
high_band_output = f"{split_band_path}/ref_high_band_slc.h5"
# secondary SLC
else:
low_band_output = f"{split_band_path}/sec_low_band_slc.h5"
high_band_output = f"{split_band_path}/sec_high_band_slc.h5"
# Open RSLC product
slc_product = SLC(hdf5file=hdf5_str)
# Extract metadata
# meta data extraction
meta_data = splitspectrum.bandpass_meta_data.load_from_slc(
slc_product=slc_product,
freq=freq)
bandwidth_half = 0.5 * meta_data.rg_bandwidth
low_frequency_slc = meta_data.center_freq - bandwidth_half
high_frequency_slc = meta_data.center_freq + bandwidth_half
# first and second elements are the frequency ranges for low and high sub-bands, respectively.
low_subband_frequencies = np.array(
[low_frequency_slc, low_frequency_slc + low_band_bandwidth])
high_subband_frequencies = np.array(
[high_frequency_slc - high_band_bandwidth, high_frequency_slc])
low_band_center_freq = low_frequency_slc + low_band_bandwidth/2
high_band_center_freq = high_frequency_slc - high_band_bandwidth/2
# Specify split-spectrum parameters
split_spectrum_parameters = splitspectrum.SplitSpectrum(
rg_sample_freq=meta_data.rg_sample_freq,
rg_bandwidth=meta_data.rg_bandwidth,
center_frequency=meta_data.center_freq,
slant_range=meta_data.slant_range,
freq=freq)
dest_freq_path = os.path.join(slc_product.SwathPath,
f'frequency{freq}')
# prepare HDF5 for subband SLC HDF5
prep_subband_h5(hdf5_str, low_band_output, iono_freq_pol)
prep_subband_h5(hdf5_str, high_band_output, iono_freq_pol)
with h5py.File(hdf5_str, 'r', libver='latest', swmr=True) as src_h5, \
h5py.File(low_band_output, 'r+') as dst_h5_low, \
h5py.File(high_band_output, 'r+') as dst_h5_high:
# Copy HDF5 metadata for low high band
# cp_h5_meta_data(src_h5, dst_h5_low, f'{common_parent_path}')
# cp_h5_meta_data(src_h5, dst_h5_high, f'{common_parent_path}')
for pol in pol_list:
raster_str = f'HDF5:{hdf5_str}:/{slc_product.slcPath(freq, pol)}'
slc_raster = isce3.io.Raster(raster_str)
rows = slc_raster.length
cols = slc_raster.width
nblocks = int(np.ceil(rows / blocksize))
fft_size = cols
for block in range(0, nblocks):
info_channel.log(f" split_spectrum block: {block}")
row_start = block * blocksize
if ((row_start + blocksize) > rows):
block_rows_data = rows - row_start
else:
block_rows_data = blocksize
dest_pol_path = f"{dest_freq_path}/{pol}"
target_slc_image = np.empty([block_rows_data, cols],
dtype=complex)
src_h5[dest_pol_path].read_direct(
target_slc_image,
np.s_[row_start: row_start + block_rows_data, :])
subband_slc_low, subband_meta_low = \
split_spectrum_parameters.bandpass_shift_spectrum(
slc_raster=target_slc_image,
low_frequency=low_subband_frequencies[0],
high_frequency=low_subband_frequencies[1],
new_center_frequency=low_band_center_freq,
fft_size=fft_size,
window_shape=window_shape,
window_function=window_function,
resampling=False
)
subband_slc_high, subband_meta_high = \
split_spectrum_parameters.bandpass_shift_spectrum(
slc_raster=target_slc_image,
low_frequency=high_subband_frequencies[0],
high_frequency=high_subband_frequencies[1],
new_center_frequency=high_band_center_freq,
fft_size=fft_size,
window_shape=window_shape,
window_function=window_function,
resampling=False
)
if block == 0:
del dst_h5_low[dest_pol_path]
del dst_h5_high[dest_pol_path]
# Initialize the raster with updated shape in HDF5
dst_h5_low.create_dataset(dest_pol_path,
[rows, cols],
np.complex64,
chunks=(128, 128))
dst_h5_high.create_dataset(dest_pol_path,
[rows, cols],
np.complex64,
chunks=(128, 128))
# Write bandpassed SLC to HDF5
dst_h5_low[dest_pol_path].write_direct(
subband_slc_low,
dest_sel=np.s_[
row_start: row_start + block_rows_data, :])
dst_h5_high[dest_pol_path].write_direct(
subband_slc_high,
dest_sel=np.s_[
row_start: row_start + block_rows_data, :])
dst_h5_low[dest_pol_path].attrs[
'description'] = f"Split-spectrum SLC image ({pol})"
dst_h5_low[dest_pol_path].attrs['units'] = f""
dst_h5_high[dest_pol_path].attrs[
'description'] = f"Split-spectrum SLC image ({pol})"
dst_h5_high[dest_pol_path].attrs['units'] = f""
# update meta information for bandpass SLC
data = dst_h5_low[f"{dest_freq_path}/processedCenterFrequency"]
data[...] = subband_meta_low['center_frequency']
data = dst_h5_low[f"{dest_freq_path}/processedRangeBandwidth"]
data[...] = subband_meta_low['rg_bandwidth']
data = dst_h5_high[f"{dest_freq_path}/processedCenterFrequency"]
data[...] = subband_meta_high['center_frequency']
data = dst_h5_high[f"{dest_freq_path}/processedRangeBandwidth"]
data[...] = subband_meta_high['rg_bandwidth']
else:
info_channel.log('Split spectrum is not needed')
t_all_elapsed = time.time() - t_all
info_channel.log(
f"successfully ran split_spectrum in {t_all_elapsed:.3f} seconds")
if __name__ == "__main__":
'''
Run split-spectrum from command line
'''
# load command line args
split_spectrum_parser = YamlArgparse()
args = split_spectrum_parser.parse()
# get a runconfig dict from command line args
split_spectrum_runconfig = SplitSpectrumRunConfig(args)
# run bandpass
run(split_spectrum_runconfig.cfg)
| #!/usr/bin/env python3
import os
import pathlib
import time
import h5py
import isce3
import journal
import numpy as np
from isce3.splitspectrum import splitspectrum
from nisar.h5 import cp_h5_meta_data
from nisar.products.readers import SLC
from nisar.workflows.split_spectrum_runconfig import SplitSpectrumRunConfig
from nisar.workflows.yaml_argparse import YamlArgparse
def prep_subband_h5(full_hdf5: str,
sub_band_hdf5: str,
freq_pols):
common_parent_path = 'science/LSAR'
swath_path = f'{common_parent_path}/SLC/swaths/'
freq_a_path = f'{swath_path}/frequencyA/'
freq_b_path = f'{swath_path}/frequencyB/'
metadata_path = f'{common_parent_path}/SLC/metadata/'
ident_path = f'{common_parent_path}/identification/'
pol_a_path = f'{freq_a_path}/listOfPolarizations'
pol_b_path = f'{freq_b_path}/listOfPolarizations'
with h5py.File(full_hdf5, 'r', libver='latest', swmr=True) as src_h5, \
h5py.File(sub_band_hdf5, 'w') as dst_h5:
pols_freqA = list(
np.array(src_h5[pol_a_path][()], dtype=str))
pols_freqB = list(
np.array(src_h5[pol_b_path][()], dtype=str))
if freq_pols['A']:
pols_a_excludes = [pol for pol in pols_freqA
if pol not in freq_pols['A']]
else:
pols_a_excludes = pols_freqA
if freq_pols['B']:
pols_b_excludes = [pol for pol in pols_freqB
if pol not in freq_pols['B']]
else:
pols_b_excludes = pols_freqB
if pols_a_excludes:
cp_h5_meta_data(src_h5, dst_h5, freq_a_path,
excludes=pols_a_excludes)
else:
cp_h5_meta_data(src_h5, dst_h5, freq_a_path,
excludes=[''])
if pols_b_excludes:
cp_h5_meta_data(src_h5, dst_h5, freq_b_path,
excludes=pols_b_excludes)
else:
cp_h5_meta_data(src_h5, dst_h5, freq_b_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, metadata_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, ident_path,
excludes=[''])
cp_h5_meta_data(src_h5, dst_h5, swath_path,
excludes=['frequencyA', 'frequencyB'])
def run(cfg: dict):
'''
run bandpass
'''
# pull parameters from cfg
ref_hdf5 = cfg['input_file_group']['reference_rslc_file_path']
sec_hdf5 = cfg['input_file_group']['secondary_rslc_file_path']
# Extract range split spectrum dictionary and corresponding parameters
ionosphere_option = cfg['processing']['ionosphere_phase_correction']
method = ionosphere_option['spectral_diversity']
split_cfg = ionosphere_option['split_range_spectrum']
iono_freq_pol = ionosphere_option['list_of_frequencies']
blocksize = split_cfg['lines_per_block']
window_function = split_cfg['window_function']
window_shape = split_cfg['window_shape']
low_band_bandwidth = split_cfg['low_band_bandwidth']
high_band_bandwidth = split_cfg['high_band_bandwidth']
scratch_path = pathlib.Path(cfg['product_path_group']['scratch_path'])
info_channel = journal.info("split_spectrum.run")
info_channel.log("starting split_spectrum")
t_all = time.time()
# Check split spectrum method
if method == 'split_main_band':
split_band_path = pathlib.Path(
f"{scratch_path}/ionosphere/split_spectrum/")
split_band_path.mkdir(parents=True, exist_ok=True)
common_parent_path = 'science/LSAR'
freq = 'A'
pol_list = iono_freq_pol[freq]
info_channel.log(f'Split the main band {pol_list} of the signal')
for hdf5_ind, hdf5_str in enumerate([ref_hdf5, sec_hdf5]):
# reference SLC
if hdf5_ind == 0:
low_band_output = f"{split_band_path}/ref_low_band_slc.h5"
high_band_output = f"{split_band_path}/ref_high_band_slc.h5"
# secondary SLC
else:
low_band_output = f"{split_band_path}/sec_low_band_slc.h5"
high_band_output = f"{split_band_path}/sec_high_band_slc.h5"
# Open RSLC product
slc_product = SLC(hdf5file=hdf5_str)
# Extract metadata
# meta data extraction
meta_data = splitspectrum.bandpass_meta_data.load_from_slc(
slc_product=slc_product,
freq=freq)
bandwidth_half = 0.5 * meta_data.rg_bandwidth
low_frequency_slc = meta_data.center_freq - bandwidth_half
high_frequency_slc = meta_data.center_freq + bandwidth_half
# first and second elements are the frequency ranges for low and high sub-bands, respectively.
low_subband_frequencies = np.array(
[low_frequency_slc, low_frequency_slc + low_band_bandwidth])
high_subband_frequencies = np.array(
[high_frequency_slc - high_band_bandwidth, high_frequency_slc])
low_band_center_freq = low_frequency_slc + low_band_bandwidth/2
high_band_center_freq = high_frequency_slc - high_band_bandwidth/2
# Specify split-spectrum parameters
split_spectrum_parameters = splitspectrum.SplitSpectrum(
rg_sample_freq=meta_data.rg_sample_freq,
rg_bandwidth=meta_data.rg_bandwidth,
center_frequency=meta_data.center_freq,
slant_range=meta_data.slant_range,
freq=freq)
dest_freq_path = os.path.join(slc_product.SwathPath,
f'frequency{freq}')
# prepare HDF5 for subband SLC HDF5
prep_subband_h5(hdf5_str, low_band_output, iono_freq_pol)
prep_subband_h5(hdf5_str, high_band_output, iono_freq_pol)
with h5py.File(hdf5_str, 'r', libver='latest', swmr=True) as src_h5, \
h5py.File(low_band_output, 'r+') as dst_h5_low, \
h5py.File(high_band_output, 'r+') as dst_h5_high:
# Copy HDF5 metadata for low high band
# cp_h5_meta_data(src_h5, dst_h5_low, f'{common_parent_path}')
# cp_h5_meta_data(src_h5, dst_h5_high, f'{common_parent_path}')
for pol in pol_list:
raster_str = f'HDF5:{hdf5_str}:/{slc_product.slcPath(freq, pol)}'
slc_raster = isce3.io.Raster(raster_str)
rows = slc_raster.length
cols = slc_raster.width
nblocks = int(np.ceil(rows / blocksize))
fft_size = cols
for block in range(0, nblocks):
info_channel.log(f" split_spectrum block: {block}")
row_start = block * blocksize
if ((row_start + blocksize) > rows):
block_rows_data = rows - row_start
else:
block_rows_data = blocksize
dest_pol_path = f"{dest_freq_path}/{pol}"
target_slc_image = np.empty([block_rows_data, cols],
dtype=complex)
src_h5[dest_pol_path].read_direct(
target_slc_image,
np.s_[row_start: row_start + block_rows_data, :])
subband_slc_low, subband_meta_low = \
split_spectrum_parameters.bandpass_shift_spectrum(
slc_raster=target_slc_image,
low_frequency=low_subband_frequencies[0],
high_frequency=low_subband_frequencies[1],
new_center_frequency=low_band_center_freq,
fft_size=fft_size,
window_shape=window_shape,
window_function=window_function,
resampling=False
)
subband_slc_high, subband_meta_high = \
split_spectrum_parameters.bandpass_shift_spectrum(
slc_raster=target_slc_image,
low_frequency=high_subband_frequencies[0],
high_frequency=high_subband_frequencies[1],
new_center_frequency=high_band_center_freq,
fft_size=fft_size,
window_shape=window_shape,
window_function=window_function,
resampling=False
)
if block == 0:
del dst_h5_low[dest_pol_path]
del dst_h5_high[dest_pol_path]
# Initialize the raster with updated shape in HDF5
dst_h5_low.create_dataset(dest_pol_path,
[rows, cols],
np.complex64,
chunks=(128, 128))
dst_h5_high.create_dataset(dest_pol_path,
[rows, cols],
np.complex64,
chunks=(128, 128))
# Write bandpassed SLC to HDF5
dst_h5_low[dest_pol_path].write_direct(
subband_slc_low,
dest_sel=np.s_[
row_start: row_start + block_rows_data, :])
dst_h5_high[dest_pol_path].write_direct(
subband_slc_high,
dest_sel=np.s_[
row_start: row_start + block_rows_data, :])
dst_h5_low[dest_pol_path].attrs[
'description'] = f"Split-spectrum SLC image ({pol})"
dst_h5_low[dest_pol_path].attrs['units'] = f""
dst_h5_high[dest_pol_path].attrs[
'description'] = f"Split-spectrum SLC image ({pol})"
dst_h5_high[dest_pol_path].attrs['units'] = f""
# update meta information for bandpass SLC
data = dst_h5_low[f"{dest_freq_path}/processedCenterFrequency"]
data[...] = subband_meta_low['center_frequency']
data = dst_h5_low[f"{dest_freq_path}/processedRangeBandwidth"]
data[...] = subband_meta_low['rg_bandwidth']
data = dst_h5_high[f"{dest_freq_path}/processedCenterFrequency"]
data[...] = subband_meta_high['center_frequency']
data = dst_h5_high[f"{dest_freq_path}/processedRangeBandwidth"]
data[...] = subband_meta_high['rg_bandwidth']
else:
info_channel.log('Split spectrum is not needed')
t_all_elapsed = time.time() - t_all
info_channel.log(
f"successfully ran split_spectrum in {t_all_elapsed:.3f} seconds")
if __name__ == "__main__":
'''
Run split-spectrum from command line
'''
# load command line args
split_spectrum_parser = YamlArgparse()
args = split_spectrum_parser.parse()
# get a runconfig dict from command line args
split_spectrum_runconfig = SplitSpectrumRunConfig(args)
# run bandpass
run(split_spectrum_runconfig.cfg)
| en | 0.560171 | #!/usr/bin/env python3 run bandpass # pull parameters from cfg # Extract range split spectrum dictionary and corresponding parameters # Check split spectrum method # reference SLC # secondary SLC # Open RSLC product # Extract metadata # meta data extraction # first and second elements are the frequency ranges for low and high sub-bands, respectively. # Specify split-spectrum parameters # prepare HDF5 for subband SLC HDF5 # Copy HDF5 metadata for low high band # cp_h5_meta_data(src_h5, dst_h5_low, f'{common_parent_path}') # cp_h5_meta_data(src_h5, dst_h5_high, f'{common_parent_path}') # Initialize the raster with updated shape in HDF5 # Write bandpassed SLC to HDF5 # update meta information for bandpass SLC Run split-spectrum from command line # load command line args # get a runconfig dict from command line args # run bandpass | 1.821961 | 2 |
demopytest/demopytest.py | SimJoonYeol/pytestdemo | 0 | 6620598 | # -*- coding: utf-8 -*-
def demo_method(num):
num += 1
return num
def demo_raise():
import rospy
class demo_class(object):
def demo_plus_10(self, num):
num += 10
return num
def demo_minus_10(self, num):
num -= 10
return num
def get_collections():
from demopytest import demomock
collections = demomock.get_mongodb()
result = ''
for collection in collections:
result += collection
return result
| # -*- coding: utf-8 -*-
def demo_method(num):
num += 1
return num
def demo_raise():
import rospy
class demo_class(object):
def demo_plus_10(self, num):
num += 10
return num
def demo_minus_10(self, num):
num -= 10
return num
def get_collections():
from demopytest import demomock
collections = demomock.get_mongodb()
result = ''
for collection in collections:
result += collection
return result
| en | 0.769321 | # -*- coding: utf-8 -*- | 3.041318 | 3 |
poco/scripts/extract_unidentified_keywords.py | sunliwen/poco | 0 | 6620599 | <reponame>sunliwen/poco<gh_stars>0
import sys
import os.path
from apps.apis.search.keyword_list import keyword_list
def run(site_id, path):
print "Note: "
print " 1. add '#' to a line to black list a keyword"
print " 2. lines without '#' would be treated as white listed"
print " 3. some lines are pre-marked as black listed. You may adjust this by removing the '#'"
answer = raw_input("Do you really want to extract unidentified keyword file for site: %s to path: %s?(enter 'yes' to continue)" % (site_id, path))
if answer == "yes":
f_add_to_whitelist = open(path, "w")
for record in keyword_list.fetchSuggestKeywordList(site_id):
keyword = record["keyword"].encode("utf8")
#if record["type"] == keyword_list.WHITE_LIST:
# f_white.write("%s\n" % keyword)
#elif record["type"] == keyword_list.BLACK_LIST:
# f_black.write("%s\n" % keyword)
if record["type"] == keyword_list.UNIDENTIFIED_LIST:
if len(record["keyword"]) < 2 or record["count"] < 3:
f_add_to_whitelist.write("#%s\n" % keyword)
else:
f_add_to_whitelist.write("%s\n" % keyword)
f_add_to_whitelist.close()
print "Finished."
else:
print "Exit without action."
sys.exit(0)
| import sys
import os.path
from apps.apis.search.keyword_list import keyword_list
def run(site_id, path):
print "Note: "
print " 1. add '#' to a line to black list a keyword"
print " 2. lines without '#' would be treated as white listed"
print " 3. some lines are pre-marked as black listed. You may adjust this by removing the '#'"
answer = raw_input("Do you really want to extract unidentified keyword file for site: %s to path: %s?(enter 'yes' to continue)" % (site_id, path))
if answer == "yes":
f_add_to_whitelist = open(path, "w")
for record in keyword_list.fetchSuggestKeywordList(site_id):
keyword = record["keyword"].encode("utf8")
#if record["type"] == keyword_list.WHITE_LIST:
# f_white.write("%s\n" % keyword)
#elif record["type"] == keyword_list.BLACK_LIST:
# f_black.write("%s\n" % keyword)
if record["type"] == keyword_list.UNIDENTIFIED_LIST:
if len(record["keyword"]) < 2 or record["count"] < 3:
f_add_to_whitelist.write("#%s\n" % keyword)
else:
f_add_to_whitelist.write("%s\n" % keyword)
f_add_to_whitelist.close()
print "Finished."
else:
print "Exit without action."
sys.exit(0) | en | 0.172025 | #if record["type"] == keyword_list.WHITE_LIST: # f_white.write("%s\n" % keyword) #elif record["type"] == keyword_list.BLACK_LIST: # f_black.write("%s\n" % keyword) | 3.269286 | 3 |
python/spi/parser.py | montreal91/jolly-jay | 0 | 6620600 | <reponame>montreal91/jolly-jay
from spi.errors import ParserError, ErrorCode
from spi.token import TokenType
from spi.ast import Assign
from spi.ast import BinaryOperation
from spi.ast import Block
from spi.ast import Compound
from spi.ast import NoOp
from spi.ast import Number
from spi.ast import Param
from spi.ast import ProcedureCall
from spi.ast import ProcedureDeclaration
from spi.ast import Program
from spi.ast import Var
from spi.ast import VarDeclaration
from spi.ast import Type
from spi.ast import UnaryOperation
class Parser:
def __init__(self, lexer):
self._lexer = lexer
self._parse_tree = None
# Set current token to the first token from the input
self._current_token = self._lexer.get_next_token()
def parse(self):
if self._parse_tree is not None:
return self._parse_tree
self._parse_tree = self._program()
if self._current_token.get_type() != TokenType.EOF:
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
return self._parse_tree
def _program(self):
"""
program : PROGRAM variable SEMI block DOT
"""
self._eat(TokenType.PROGRAM)
var_node = self._variable()
prog_name = var_node.value
self._eat(TokenType.SEMI)
block_node = self._block()
program_node = Program(name=prog_name, block=block_node)
self._eat(TokenType.DOT)
return program_node
def _block(self):
"""
block : declarations compound_statement
"""
declaration_nodes = self._declarations()
compound_statement_node = self._compound_statement()
return Block(
declarations=declaration_nodes,
compound_statement=compound_statement_node
)
def _declarations(self):
"""
declarations : (VAR (variable_declaration SEMI)+)?
| procedure_declaration*
| empty
"""
declarations = []
while self._current_token.get_type() == TokenType.VAR:
self._eat(TokenType.VAR)
while self._current_token.get_type() == TokenType.ID:
var_decl = self._variable_declaration()
declarations.extend(var_decl)
self._eat(TokenType.SEMI)
while self._current_token.get_type() == TokenType.PROCEDURE:
declarations.append(self._procedure_declaration())
return declarations
def _procedure_declaration(self):
"""
procedure_declaration :
PROCEDURE ID (LPAR formal_parameter_list RPAR)? SEMI block SEMI
"""
self._eat(TokenType.PROCEDURE)
proc_name = self._current_token.get_value()
self._eat(TokenType.ID)
params = []
if self._current_token.get_type() == TokenType.LPAR:
self._eat(TokenType.LPAR)
params = self._formal_parameter_list()
self._eat(TokenType.RPAR)
self._eat(TokenType.SEMI)
block_node = self._block()
proc_decl = ProcedureDeclaration(proc_name, params, block_node)
self._eat(TokenType.SEMI)
return proc_decl
def _proccall_statement(self):
"""
proccall_statement: ID LPAR (expr (COMMA expr)*)? RPAR
"""
token = self._current_token
proc_name = token.get_value()
self._eat(TokenType.ID)
self._eat(TokenType.LPAR)
actual_params = []
if self._current_token.get_type() != TokenType.RPAR:
node = self._expr()
actual_params.append(node)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
node = self._expr()
actual_params.append(node)
self._eat(TokenType.RPAR)
return ProcedureCall(
proc_name=proc_name,
actual_params=actual_params,
token=token
)
def _formal_parameter_list(self):
"""
formal_parameter_list : formal_parameters
| formal_parameters SEMI formal_parameter_list
"""
parameters = self._formal_parameters()
if self._current_token.get_type() == TokenType.SEMI:
self._eat(TokenType.SEMI)
parameters.extend(self._formal_parameter_list())
return parameters
def _formal_parameters(self):
"""
formal_parameters : ID (COMMA ID)* COLON type_spec
"""
param_nodes = [Var(self._current_token)]
self._eat(TokenType.ID)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
param_nodes.append(Var(self._current_token))
self._eat(TokenType.ID)
self._eat(TokenType.COLON)
type_node = self._type_spec()
return [
Param(var_node, type_node) for var_node in param_nodes
]
def _variable_declaration(self):
"""
variable_declaration : ID (COMMA ID)* COLON type_spec
"""
var_nodes = [Var(self._current_token)] # first ID
self._eat(TokenType.ID)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
var_nodes.append(Var(self._current_token))
self._eat(TokenType.ID)
self._eat(TokenType.COLON)
type_node = self._type_spec()
return tuple(
VarDeclaration(var_node, type_node) for var_node in var_nodes
)
def _type_spec(self):
"""
type_spec : INTEGER | REAL
"""
token = self._current_token
if self._current_token.get_type() == TokenType.INTEGER:
self._eat(TokenType.INTEGER)
elif self._current_token.get_type() == TokenType.REAL:
self._eat(TokenType.REAL)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
return Type(token)
def _compound_statement(self):
"""
compound_statement: BEGIN statement_list END
"""
self._eat(TokenType.BEGIN)
nodes = self._statement_list()
self._eat(TokenType.END)
root = Compound()
for node in nodes:
root.children.append(node)
return root
def _statement_list(self):
"""
statement_list : statement
| statement SEMI statement_list
"""
node = self._statement()
results = [node]
while self._current_token.get_type() == TokenType.SEMI:
self._eat(TokenType.SEMI)
results.append(self._statement())
if self._current_token.get_type() == TokenType.ID:
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
return results
def _statement(self):
"""
statement : compound_statement
| proccall_statement
| assignment_statement
| empty
"""
if self._current_token.get_type() == TokenType.BEGIN:
node = self._compound_statement()
elif self._current_token.get_type() == TokenType.ID:
if self._lexer.get_current_char() == '(':
node = self._proccall_statement()
else:
node = self._assignment_statement()
else:
node = self._empty()
return node
def _assignment_statement(self):
"""
assignment_statement : variable ASSIGN expr
"""
left = self._variable()
token = self._current_token
self._eat(TokenType.ASSIGN)
right = self._expr()
return Assign(left=left, op=token, right=right)
def _variable(self):
"""
variable : ID
"""
node = Var(self._current_token)
self._eat(TokenType.ID)
return node
@staticmethod
def _empty():
"""
An empty production.
"""
return NoOp()
def _expr(self):
"""
Process expr production.
expr : operand ((PLUS | MINUS) operand)*
"""
node = self._operand()
while self._current_token.get_type() in (TokenType.PLUS, TokenType.MINUS):
token = self._current_token
if token.get_type() == TokenType.PLUS:
self._eat(TokenType.PLUS)
elif token.get_type() == TokenType.MINUS:
self._eat(TokenType.MINUS)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
node = BinaryOperation(left=node, op=token, right=self._operand())
return node
def _operand(self):
"""
Process operand production.
operand : factor ((MULTIPLY | INTEGER_DIV | REAL_DIV) factor)*
"""
node = self._factor()
types = (TokenType.MULTIPLY, TokenType.INTEGER_DIV, TokenType.REAL_DIV)
while self._current_token.get_type() in types:
token = self._current_token
if token.get_type() == TokenType.MULTIPLY:
self._eat(TokenType.MULTIPLY)
elif token.get_type() == TokenType.INTEGER_DIV:
self._eat(TokenType.INTEGER_DIV)
elif token.get_type() == TokenType.REAL_DIV:
self._eat(TokenType.REAL_DIV)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
node = BinaryOperation(left=node, op=token, right=self._factor())
return node
def _factor(self):
"""
Process factor production.
factor : PLUS factor
| MINUS factor
| INTEGER_LITERAL
| REAL_LITERAL
| LPAR expr RPAR
| variable
"""
token = self._current_token
if token.get_type() in (TokenType.PLUS, TokenType.MINUS):
self._eat(token.get_type())
return UnaryOperation(op=token, right=self._factor())
elif token.get_type() == TokenType.INTEGER_LITERAL:
self._eat(TokenType.INTEGER_LITERAL)
return Number(token)
elif token.get_type() == TokenType.REAL_LITERAL:
self._eat(TokenType.REAL_LITERAL)
return Number(token)
elif token.get_type() == TokenType.LPAR:
self._eat(TokenType.LPAR)
node = self._expr()
self._eat(TokenType.RPAR)
return node
elif token.get_type() == TokenType.ID:
# ???
return self._variable()
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
def _eat(self, token_type):
"""
'Eats' current token if it is of expected type.
Compare the current token type with the passed token
type and if they match then "eat" the current token
and assign the next token to the self._current_token,
otherwise raise an exception.
"""
if self._current_token.get_type() == token_type:
self._current_token = self._lexer.get_next_token()
else:
print(
f"expected type was {token_type} "
f"got {self._current_token.get_type()}"
)
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
def _error(self, error_code, token):
raise ParserError(
error_code=error_code,
token=token,
message=f"{error_code.value} -> {token}",
)
| from spi.errors import ParserError, ErrorCode
from spi.token import TokenType
from spi.ast import Assign
from spi.ast import BinaryOperation
from spi.ast import Block
from spi.ast import Compound
from spi.ast import NoOp
from spi.ast import Number
from spi.ast import Param
from spi.ast import ProcedureCall
from spi.ast import ProcedureDeclaration
from spi.ast import Program
from spi.ast import Var
from spi.ast import VarDeclaration
from spi.ast import Type
from spi.ast import UnaryOperation
class Parser:
def __init__(self, lexer):
self._lexer = lexer
self._parse_tree = None
# Set current token to the first token from the input
self._current_token = self._lexer.get_next_token()
def parse(self):
if self._parse_tree is not None:
return self._parse_tree
self._parse_tree = self._program()
if self._current_token.get_type() != TokenType.EOF:
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
return self._parse_tree
def _program(self):
"""
program : PROGRAM variable SEMI block DOT
"""
self._eat(TokenType.PROGRAM)
var_node = self._variable()
prog_name = var_node.value
self._eat(TokenType.SEMI)
block_node = self._block()
program_node = Program(name=prog_name, block=block_node)
self._eat(TokenType.DOT)
return program_node
def _block(self):
"""
block : declarations compound_statement
"""
declaration_nodes = self._declarations()
compound_statement_node = self._compound_statement()
return Block(
declarations=declaration_nodes,
compound_statement=compound_statement_node
)
def _declarations(self):
"""
declarations : (VAR (variable_declaration SEMI)+)?
| procedure_declaration*
| empty
"""
declarations = []
while self._current_token.get_type() == TokenType.VAR:
self._eat(TokenType.VAR)
while self._current_token.get_type() == TokenType.ID:
var_decl = self._variable_declaration()
declarations.extend(var_decl)
self._eat(TokenType.SEMI)
while self._current_token.get_type() == TokenType.PROCEDURE:
declarations.append(self._procedure_declaration())
return declarations
def _procedure_declaration(self):
"""
procedure_declaration :
PROCEDURE ID (LPAR formal_parameter_list RPAR)? SEMI block SEMI
"""
self._eat(TokenType.PROCEDURE)
proc_name = self._current_token.get_value()
self._eat(TokenType.ID)
params = []
if self._current_token.get_type() == TokenType.LPAR:
self._eat(TokenType.LPAR)
params = self._formal_parameter_list()
self._eat(TokenType.RPAR)
self._eat(TokenType.SEMI)
block_node = self._block()
proc_decl = ProcedureDeclaration(proc_name, params, block_node)
self._eat(TokenType.SEMI)
return proc_decl
def _proccall_statement(self):
"""
proccall_statement: ID LPAR (expr (COMMA expr)*)? RPAR
"""
token = self._current_token
proc_name = token.get_value()
self._eat(TokenType.ID)
self._eat(TokenType.LPAR)
actual_params = []
if self._current_token.get_type() != TokenType.RPAR:
node = self._expr()
actual_params.append(node)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
node = self._expr()
actual_params.append(node)
self._eat(TokenType.RPAR)
return ProcedureCall(
proc_name=proc_name,
actual_params=actual_params,
token=token
)
def _formal_parameter_list(self):
"""
formal_parameter_list : formal_parameters
| formal_parameters SEMI formal_parameter_list
"""
parameters = self._formal_parameters()
if self._current_token.get_type() == TokenType.SEMI:
self._eat(TokenType.SEMI)
parameters.extend(self._formal_parameter_list())
return parameters
def _formal_parameters(self):
"""
formal_parameters : ID (COMMA ID)* COLON type_spec
"""
param_nodes = [Var(self._current_token)]
self._eat(TokenType.ID)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
param_nodes.append(Var(self._current_token))
self._eat(TokenType.ID)
self._eat(TokenType.COLON)
type_node = self._type_spec()
return [
Param(var_node, type_node) for var_node in param_nodes
]
def _variable_declaration(self):
"""
variable_declaration : ID (COMMA ID)* COLON type_spec
"""
var_nodes = [Var(self._current_token)] # first ID
self._eat(TokenType.ID)
while self._current_token.get_type() == TokenType.COMMA:
self._eat(TokenType.COMMA)
var_nodes.append(Var(self._current_token))
self._eat(TokenType.ID)
self._eat(TokenType.COLON)
type_node = self._type_spec()
return tuple(
VarDeclaration(var_node, type_node) for var_node in var_nodes
)
def _type_spec(self):
"""
type_spec : INTEGER | REAL
"""
token = self._current_token
if self._current_token.get_type() == TokenType.INTEGER:
self._eat(TokenType.INTEGER)
elif self._current_token.get_type() == TokenType.REAL:
self._eat(TokenType.REAL)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
return Type(token)
def _compound_statement(self):
"""
compound_statement: BEGIN statement_list END
"""
self._eat(TokenType.BEGIN)
nodes = self._statement_list()
self._eat(TokenType.END)
root = Compound()
for node in nodes:
root.children.append(node)
return root
def _statement_list(self):
"""
statement_list : statement
| statement SEMI statement_list
"""
node = self._statement()
results = [node]
while self._current_token.get_type() == TokenType.SEMI:
self._eat(TokenType.SEMI)
results.append(self._statement())
if self._current_token.get_type() == TokenType.ID:
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
return results
def _statement(self):
"""
statement : compound_statement
| proccall_statement
| assignment_statement
| empty
"""
if self._current_token.get_type() == TokenType.BEGIN:
node = self._compound_statement()
elif self._current_token.get_type() == TokenType.ID:
if self._lexer.get_current_char() == '(':
node = self._proccall_statement()
else:
node = self._assignment_statement()
else:
node = self._empty()
return node
def _assignment_statement(self):
"""
assignment_statement : variable ASSIGN expr
"""
left = self._variable()
token = self._current_token
self._eat(TokenType.ASSIGN)
right = self._expr()
return Assign(left=left, op=token, right=right)
def _variable(self):
"""
variable : ID
"""
node = Var(self._current_token)
self._eat(TokenType.ID)
return node
@staticmethod
def _empty():
"""
An empty production.
"""
return NoOp()
def _expr(self):
"""
Process expr production.
expr : operand ((PLUS | MINUS) operand)*
"""
node = self._operand()
while self._current_token.get_type() in (TokenType.PLUS, TokenType.MINUS):
token = self._current_token
if token.get_type() == TokenType.PLUS:
self._eat(TokenType.PLUS)
elif token.get_type() == TokenType.MINUS:
self._eat(TokenType.MINUS)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
node = BinaryOperation(left=node, op=token, right=self._operand())
return node
def _operand(self):
"""
Process operand production.
operand : factor ((MULTIPLY | INTEGER_DIV | REAL_DIV) factor)*
"""
node = self._factor()
types = (TokenType.MULTIPLY, TokenType.INTEGER_DIV, TokenType.REAL_DIV)
while self._current_token.get_type() in types:
token = self._current_token
if token.get_type() == TokenType.MULTIPLY:
self._eat(TokenType.MULTIPLY)
elif token.get_type() == TokenType.INTEGER_DIV:
self._eat(TokenType.INTEGER_DIV)
elif token.get_type() == TokenType.REAL_DIV:
self._eat(TokenType.REAL_DIV)
else:
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
node = BinaryOperation(left=node, op=token, right=self._factor())
return node
def _factor(self):
"""
Process factor production.
factor : PLUS factor
| MINUS factor
| INTEGER_LITERAL
| REAL_LITERAL
| LPAR expr RPAR
| variable
"""
token = self._current_token
if token.get_type() in (TokenType.PLUS, TokenType.MINUS):
self._eat(token.get_type())
return UnaryOperation(op=token, right=self._factor())
elif token.get_type() == TokenType.INTEGER_LITERAL:
self._eat(TokenType.INTEGER_LITERAL)
return Number(token)
elif token.get_type() == TokenType.REAL_LITERAL:
self._eat(TokenType.REAL_LITERAL)
return Number(token)
elif token.get_type() == TokenType.LPAR:
self._eat(TokenType.LPAR)
node = self._expr()
self._eat(TokenType.RPAR)
return node
elif token.get_type() == TokenType.ID:
# ???
return self._variable()
self._error(error_code=ErrorCode.UNEXPECTED_TOKEN, token=token)
def _eat(self, token_type):
"""
'Eats' current token if it is of expected type.
Compare the current token type with the passed token
type and if they match then "eat" the current token
and assign the next token to the self._current_token,
otherwise raise an exception.
"""
if self._current_token.get_type() == token_type:
self._current_token = self._lexer.get_next_token()
else:
print(
f"expected type was {token_type} "
f"got {self._current_token.get_type()}"
)
self._error(
error_code=ErrorCode.UNEXPECTED_TOKEN,
token=self._current_token
)
def _error(self, error_code, token):
raise ParserError(
error_code=error_code,
token=token,
message=f"{error_code.value} -> {token}",
) | en | 0.536399 | # Set current token to the first token from the input program : PROGRAM variable SEMI block DOT block : declarations compound_statement declarations : (VAR (variable_declaration SEMI)+)? | procedure_declaration* | empty procedure_declaration : PROCEDURE ID (LPAR formal_parameter_list RPAR)? SEMI block SEMI proccall_statement: ID LPAR (expr (COMMA expr)*)? RPAR formal_parameter_list : formal_parameters | formal_parameters SEMI formal_parameter_list formal_parameters : ID (COMMA ID)* COLON type_spec variable_declaration : ID (COMMA ID)* COLON type_spec # first ID type_spec : INTEGER | REAL compound_statement: BEGIN statement_list END statement_list : statement | statement SEMI statement_list statement : compound_statement | proccall_statement | assignment_statement | empty assignment_statement : variable ASSIGN expr variable : ID An empty production. Process expr production. expr : operand ((PLUS | MINUS) operand)* Process operand production. operand : factor ((MULTIPLY | INTEGER_DIV | REAL_DIV) factor)* Process factor production. factor : PLUS factor | MINUS factor | INTEGER_LITERAL | REAL_LITERAL | LPAR expr RPAR | variable # ??? 'Eats' current token if it is of expected type. Compare the current token type with the passed token type and if they match then "eat" the current token and assign the next token to the self._current_token, otherwise raise an exception. | 2.586588 | 3 |
setup.py | 7starsea/shark | 0 | 6620601 |
from skbuild import setup
from setuptools import find_packages
# # python setup.py install --generator "Sublime Text 2 - Unix Makefiles" -- -- -j8
# # python setup.py install -- -- -j8
package_folder = 'shark'
setup(
name='shark',
version='0.0.1',
description='reinforcement learning project shark',
author='<NAME>',
author_email='<EMAIL>,<EMAIL>',
license='MIT',
python_requires='>=3.6',
packages=find_packages(exclude=("test", "test.*", "docs", "docs.*")), # same as name
cmake_source_dir="shark",
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 3 - Alpha',
# Indicate who your project is intended for
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Software Development :: Libraries :: Python Modules',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: MIT License',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
],
keywords='reinforcement learning project pytorch',
# install_requires=[
# 'gym>=0.15.0',
# 'tqdm',
# 'numpy',
# 'tensorboard',
# 'torch>=1.2.0',
# ],
)
# print(find_packages())
|
from skbuild import setup
from setuptools import find_packages
# # python setup.py install --generator "Sublime Text 2 - Unix Makefiles" -- -- -j8
# # python setup.py install -- -- -j8
package_folder = 'shark'
setup(
name='shark',
version='0.0.1',
description='reinforcement learning project shark',
author='<NAME>',
author_email='<EMAIL>,<EMAIL>',
license='MIT',
python_requires='>=3.6',
packages=find_packages(exclude=("test", "test.*", "docs", "docs.*")), # same as name
cmake_source_dir="shark",
classifiers=[
# How mature is this project? Common values are
# 3 - Alpha
# 4 - Beta
# 5 - Production/Stable
'Development Status :: 3 - Alpha',
# Indicate who your project is intended for
'Intended Audience :: Science/Research',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Software Development :: Libraries :: Python Modules',
# Pick your license as you wish (should match "license" above)
'License :: OSI Approved :: MIT License',
# Specify the Python versions you support here. In particular, ensure
# that you indicate whether you support Python 2, Python 3 or both.
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
'Programming Language :: Python :: 3.8',
],
keywords='reinforcement learning project pytorch',
# install_requires=[
# 'gym>=0.15.0',
# 'tqdm',
# 'numpy',
# 'tensorboard',
# 'torch>=1.2.0',
# ],
)
# print(find_packages())
| en | 0.627823 | # # python setup.py install --generator "Sublime Text 2 - Unix Makefiles" -- -- -j8 # # python setup.py install -- -- -j8 # same as name # How mature is this project? Common values are # 3 - Alpha # 4 - Beta # 5 - Production/Stable # Indicate who your project is intended for # Pick your license as you wish (should match "license" above) # Specify the Python versions you support here. In particular, ensure # that you indicate whether you support Python 2, Python 3 or both. # install_requires=[ # 'gym>=0.15.0', # 'tqdm', # 'numpy', # 'tensorboard', # 'torch>=1.2.0', # ], # print(find_packages()) | 1.687061 | 2 |
git/remote.py | swallat/GitPython | 1 | 6620602 | <reponame>swallat/GitPython
# remote.py
# Copyright (C) 2008, 2009 <NAME> (<EMAIL>) and contributors
#
# This module is part of GitPython and is released under
# the BSD License: http://www.opensource.org/licenses/bsd-license.php
# Module implementing a remote object allowing easy access to git remotes
from exc import GitCommandError
from ConfigParser import NoOptionError
from config import SectionConstraint
from git.util import (
LazyMixin,
Iterable,
IterableList
)
from git.db.interface import TransportDB
from refs import RemoteReference
import os
__all__ = ['Remote']
class PushInfo(object):
"""Wrapper for basic PushInfo to provide the previous interface which includes
resolved objects instead of plain shas
old_commit # object for the corresponding old_commit_sha"""
class FetchInfo(object):
"""Wrapper to restore the previous interface, resolving objects and wrapping
references"""
class Remote(LazyMixin, Iterable):
"""Provides easy read and write access to a git remote.
Everything not part of this interface is considered an option for the current
remote, allowing constructs like remote.pushurl to query the pushurl.
NOTE: When querying configuration, the configuration accessor will be cached
to speed up subsequent accesses."""
__slots__ = ( "repo", "name", "_config_reader" )
_id_attribute_ = "name"
def __init__(self, repo, name):
"""Initialize a remote instance
:param repo: The repository we are a remote of
:param name: the name of the remote, i.e. 'origin'"""
if not hasattr(repo, 'git'):
# note: at some point we could just create a git command instance ourselves
# but lets just be lazy for now
raise AssertionError("Require repository to provide a git command instance currently")
#END assert git cmd
if not isinstance(repo, TransportDB):
raise AssertionError("Require TransportDB interface implementation")
#END verify interface
self.repo = repo
self.name = name
if os.name == 'nt':
# some oddity: on windows, python 2.5, it for some reason does not realize
# that it has the config_writer property, but instead calls __getattr__
# which will not yield the expected results. 'pinging' the members
# with a dir call creates the config_writer property that we require
# ... bugs like these make me wonder wheter python really wants to be used
# for production. It doesn't happen on linux though.
dir(self)
# END windows special handling
def __getattr__(self, attr):
"""Allows to call this instance like
remote.special( *args, **kwargs) to call git-remote special self.name"""
if attr == "_config_reader":
return super(Remote, self).__getattr__(attr)
# sometimes, probably due to a bug in python itself, we are being called
# even though a slot of the same name exists
try:
return self._config_reader.get(attr)
except NoOptionError:
return super(Remote, self).__getattr__(attr)
# END handle exception
def _config_section_name(self):
return 'remote "%s"' % self.name
def _set_cache_(self, attr):
if attr == "_config_reader":
self._config_reader = SectionConstraint(self.repo.config_reader(), self._config_section_name())
else:
super(Remote, self)._set_cache_(attr)
def __str__(self):
return self.name
def __repr__(self):
return '<git.%s "%s">' % (self.__class__.__name__, self.name)
def __eq__(self, other):
return self.name == other.name
def __ne__(self, other):
return not ( self == other )
def __hash__(self):
return hash(self.name)
@classmethod
def iter_items(cls, repo):
""":return: Iterator yielding Remote objects of the given repository"""
for section in repo.config_reader("repository").sections():
if not section.startswith('remote'):
continue
lbound = section.find('"')
rbound = section.rfind('"')
if lbound == -1 or rbound == -1:
raise ValueError("Remote-Section has invalid format: %r" % section)
yield Remote(repo, section[lbound+1:rbound])
# END for each configuration section
@property
def refs(self):
"""
:return:
IterableList of RemoteReference objects. It is prefixed, allowing
you to omit the remote path portion, i.e.::
remote.refs.master # yields RemoteReference('/refs/remotes/origin/master')"""
out_refs = IterableList(RemoteReference._id_attribute_, "%s/" % self.name)
out_refs.extend(RemoteReference.list_items(self.repo, remote=self.name))
assert out_refs, "Remote %s did not have any references" % self.name
return out_refs
@property
def stale_refs(self):
"""
:return:
IterableList RemoteReference objects that do not have a corresponding
head in the remote reference anymore as they have been deleted on the
remote side, but are still available locally.
The IterableList is prefixed, hence the 'origin' must be omitted. See
'refs' property for an example."""
out_refs = IterableList(RemoteReference._id_attribute_, "%s/" % self.name)
for line in self.repo.git.remote("prune", "--dry-run", self).splitlines()[2:]:
# expecting
# * [would prune] origin/new_branch
token = " * [would prune] "
if not line.startswith(token):
raise ValueError("Could not parse git-remote prune result: %r" % line)
fqhn = "%s/%s" % (RemoteReference._common_path_default,line.replace(token, ""))
out_refs.append(RemoteReference(self.repo, fqhn))
# END for each line
return out_refs
@classmethod
def create(cls, repo, name, url, **kwargs):
"""Create a new remote to the given repository
:param repo: Repository instance that is to receive the new remote
:param name: Desired name of the remote
:param url: URL which corresponds to the remote's name
:param kwargs:
Additional arguments to be passed to the git-remote add command
:return: New Remote instance
:raise GitCommandError: in case an origin with that name already exists"""
repo.git.remote( "add", name, url, **kwargs )
return cls(repo, name)
# add is an alias
add = create
@classmethod
def remove(cls, repo, name ):
"""Remove the remote with the given name"""
repo.git.remote("rm", name)
# alias
rm = remove
def rename(self, new_name):
"""Rename self to the given new_name
:return: self """
if self.name == new_name:
return self
self.repo.git.remote("rename", self.name, new_name)
self.name = new_name
try:
del(self._config_reader) # it contains cached values, section names are different now
except AttributeError:
pass
#END handle exception
return self
def update(self, **kwargs):
"""Fetch all changes for this remote, including new branches which will
be forced in ( in case your local remote branch is not part the new remote branches
ancestry anymore ).
:param kwargs:
Additional arguments passed to git-remote update
:return: self """
self.repo.git.remote("update", self.name)
return self
def fetch(self, refspec=None, progress=None, **kwargs):
"""Fetch the latest changes for this remote
:param refspec:
A "refspec" is used by fetch and push to describe the mapping
between remote ref and local ref. They are combined with a colon in
the format <src>:<dst>, preceded by an optional plus sign, +.
For example: git fetch $URL refs/heads/master:refs/heads/origin means
"grab the master branch head from the $URL and store it as my origin
branch head". And git push $URL refs/heads/master:refs/heads/to-upstream
means "publish my master branch head as to-upstream branch at $URL".
See also git-push(1).
Taken from the git manual
:param progress: See 'push' method
:param kwargs: Additional arguments to be passed to git-fetch
:return:
IterableList(FetchInfo, ...) list of FetchInfo instances providing detailed
information about the fetch results
:note:
As fetch does not provide progress information to non-ttys, we cannot make
it available here unfortunately as in the 'push' method."""
return self.repo.fetch(self.name, refspec, progress, **kwargs)
def pull(self, refspec=None, progress=None, **kwargs):
"""Pull changes from the given branch, being the same as a fetch followed
by a merge of branch with your local branch.
:param refspec: see 'fetch' method
:param progress: see 'push' method
:param kwargs: Additional arguments to be passed to git-pull
:return: Please see 'fetch' method """
return self.repo.pull(self.name, refspec, progress, **kwargs)
def push(self, refspec=None, progress=None, **kwargs):
"""Push changes from source branch in refspec to target branch in refspec.
:param refspec: see 'fetch' method
:param progress:
Instance of type RemoteProgress allowing the caller to receive
progress information until the method returns.
If None, progress information will be discarded
:param kwargs: Additional arguments to be passed to git-push
:return:
IterableList(PushInfo, ...) iterable list of PushInfo instances, each
one informing about an individual head which had been updated on the remote
side.
If the push contains rejected heads, these will have the PushInfo.ERROR bit set
in their flags.
If the operation fails completely, the length of the returned IterableList will
be null."""
return self.repo.push(self.name, refspec, progress, **kwargs)
@property
def config_reader(self):
"""
:return:
GitConfigParser compatible object able to read options for only our remote.
Hence you may simple type config.get("pushurl") to obtain the information"""
return self._config_reader
@property
def config_writer(self):
"""
:return: GitConfigParser compatible object able to write options for this remote.
:note:
You can only own one writer at a time - delete it to release the
configuration file and make it useable by others.
To assure consistent results, you should only query options through the
writer. Once you are done writing, you are free to use the config reader
once again."""
writer = self.repo.config_writer()
# clear our cache to assure we re-read the possibly changed configuration
try:
del(self._config_reader)
except AttributeError:
pass
#END handle exception
return SectionConstraint(writer, self._config_section_name())
| # remote.py
# Copyright (C) 2008, 2009 <NAME> (<EMAIL>) and contributors
#
# This module is part of GitPython and is released under
# the BSD License: http://www.opensource.org/licenses/bsd-license.php
# Module implementing a remote object allowing easy access to git remotes
from exc import GitCommandError
from ConfigParser import NoOptionError
from config import SectionConstraint
from git.util import (
LazyMixin,
Iterable,
IterableList
)
from git.db.interface import TransportDB
from refs import RemoteReference
import os
__all__ = ['Remote']
class PushInfo(object):
"""Wrapper for basic PushInfo to provide the previous interface which includes
resolved objects instead of plain shas
old_commit # object for the corresponding old_commit_sha"""
class FetchInfo(object):
"""Wrapper to restore the previous interface, resolving objects and wrapping
references"""
class Remote(LazyMixin, Iterable):
"""Provides easy read and write access to a git remote.
Everything not part of this interface is considered an option for the current
remote, allowing constructs like remote.pushurl to query the pushurl.
NOTE: When querying configuration, the configuration accessor will be cached
to speed up subsequent accesses."""
__slots__ = ( "repo", "name", "_config_reader" )
_id_attribute_ = "name"
def __init__(self, repo, name):
"""Initialize a remote instance
:param repo: The repository we are a remote of
:param name: the name of the remote, i.e. 'origin'"""
if not hasattr(repo, 'git'):
# note: at some point we could just create a git command instance ourselves
# but lets just be lazy for now
raise AssertionError("Require repository to provide a git command instance currently")
#END assert git cmd
if not isinstance(repo, TransportDB):
raise AssertionError("Require TransportDB interface implementation")
#END verify interface
self.repo = repo
self.name = name
if os.name == 'nt':
# some oddity: on windows, python 2.5, it for some reason does not realize
# that it has the config_writer property, but instead calls __getattr__
# which will not yield the expected results. 'pinging' the members
# with a dir call creates the config_writer property that we require
# ... bugs like these make me wonder wheter python really wants to be used
# for production. It doesn't happen on linux though.
dir(self)
# END windows special handling
def __getattr__(self, attr):
"""Allows to call this instance like
remote.special( *args, **kwargs) to call git-remote special self.name"""
if attr == "_config_reader":
return super(Remote, self).__getattr__(attr)
# sometimes, probably due to a bug in python itself, we are being called
# even though a slot of the same name exists
try:
return self._config_reader.get(attr)
except NoOptionError:
return super(Remote, self).__getattr__(attr)
# END handle exception
def _config_section_name(self):
return 'remote "%s"' % self.name
def _set_cache_(self, attr):
if attr == "_config_reader":
self._config_reader = SectionConstraint(self.repo.config_reader(), self._config_section_name())
else:
super(Remote, self)._set_cache_(attr)
def __str__(self):
return self.name
def __repr__(self):
return '<git.%s "%s">' % (self.__class__.__name__, self.name)
def __eq__(self, other):
return self.name == other.name
def __ne__(self, other):
return not ( self == other )
def __hash__(self):
return hash(self.name)
@classmethod
def iter_items(cls, repo):
""":return: Iterator yielding Remote objects of the given repository"""
for section in repo.config_reader("repository").sections():
if not section.startswith('remote'):
continue
lbound = section.find('"')
rbound = section.rfind('"')
if lbound == -1 or rbound == -1:
raise ValueError("Remote-Section has invalid format: %r" % section)
yield Remote(repo, section[lbound+1:rbound])
# END for each configuration section
@property
def refs(self):
"""
:return:
IterableList of RemoteReference objects. It is prefixed, allowing
you to omit the remote path portion, i.e.::
remote.refs.master # yields RemoteReference('/refs/remotes/origin/master')"""
out_refs = IterableList(RemoteReference._id_attribute_, "%s/" % self.name)
out_refs.extend(RemoteReference.list_items(self.repo, remote=self.name))
assert out_refs, "Remote %s did not have any references" % self.name
return out_refs
@property
def stale_refs(self):
"""
:return:
IterableList RemoteReference objects that do not have a corresponding
head in the remote reference anymore as they have been deleted on the
remote side, but are still available locally.
The IterableList is prefixed, hence the 'origin' must be omitted. See
'refs' property for an example."""
out_refs = IterableList(RemoteReference._id_attribute_, "%s/" % self.name)
for line in self.repo.git.remote("prune", "--dry-run", self).splitlines()[2:]:
# expecting
# * [would prune] origin/new_branch
token = " * [would prune] "
if not line.startswith(token):
raise ValueError("Could not parse git-remote prune result: %r" % line)
fqhn = "%s/%s" % (RemoteReference._common_path_default,line.replace(token, ""))
out_refs.append(RemoteReference(self.repo, fqhn))
# END for each line
return out_refs
@classmethod
def create(cls, repo, name, url, **kwargs):
"""Create a new remote to the given repository
:param repo: Repository instance that is to receive the new remote
:param name: Desired name of the remote
:param url: URL which corresponds to the remote's name
:param kwargs:
Additional arguments to be passed to the git-remote add command
:return: New Remote instance
:raise GitCommandError: in case an origin with that name already exists"""
repo.git.remote( "add", name, url, **kwargs )
return cls(repo, name)
# add is an alias
add = create
@classmethod
def remove(cls, repo, name ):
"""Remove the remote with the given name"""
repo.git.remote("rm", name)
# alias
rm = remove
def rename(self, new_name):
"""Rename self to the given new_name
:return: self """
if self.name == new_name:
return self
self.repo.git.remote("rename", self.name, new_name)
self.name = new_name
try:
del(self._config_reader) # it contains cached values, section names are different now
except AttributeError:
pass
#END handle exception
return self
def update(self, **kwargs):
"""Fetch all changes for this remote, including new branches which will
be forced in ( in case your local remote branch is not part the new remote branches
ancestry anymore ).
:param kwargs:
Additional arguments passed to git-remote update
:return: self """
self.repo.git.remote("update", self.name)
return self
def fetch(self, refspec=None, progress=None, **kwargs):
"""Fetch the latest changes for this remote
:param refspec:
A "refspec" is used by fetch and push to describe the mapping
between remote ref and local ref. They are combined with a colon in
the format <src>:<dst>, preceded by an optional plus sign, +.
For example: git fetch $URL refs/heads/master:refs/heads/origin means
"grab the master branch head from the $URL and store it as my origin
branch head". And git push $URL refs/heads/master:refs/heads/to-upstream
means "publish my master branch head as to-upstream branch at $URL".
See also git-push(1).
Taken from the git manual
:param progress: See 'push' method
:param kwargs: Additional arguments to be passed to git-fetch
:return:
IterableList(FetchInfo, ...) list of FetchInfo instances providing detailed
information about the fetch results
:note:
As fetch does not provide progress information to non-ttys, we cannot make
it available here unfortunately as in the 'push' method."""
return self.repo.fetch(self.name, refspec, progress, **kwargs)
def pull(self, refspec=None, progress=None, **kwargs):
"""Pull changes from the given branch, being the same as a fetch followed
by a merge of branch with your local branch.
:param refspec: see 'fetch' method
:param progress: see 'push' method
:param kwargs: Additional arguments to be passed to git-pull
:return: Please see 'fetch' method """
return self.repo.pull(self.name, refspec, progress, **kwargs)
def push(self, refspec=None, progress=None, **kwargs):
"""Push changes from source branch in refspec to target branch in refspec.
:param refspec: see 'fetch' method
:param progress:
Instance of type RemoteProgress allowing the caller to receive
progress information until the method returns.
If None, progress information will be discarded
:param kwargs: Additional arguments to be passed to git-push
:return:
IterableList(PushInfo, ...) iterable list of PushInfo instances, each
one informing about an individual head which had been updated on the remote
side.
If the push contains rejected heads, these will have the PushInfo.ERROR bit set
in their flags.
If the operation fails completely, the length of the returned IterableList will
be null."""
return self.repo.push(self.name, refspec, progress, **kwargs)
@property
def config_reader(self):
"""
:return:
GitConfigParser compatible object able to read options for only our remote.
Hence you may simple type config.get("pushurl") to obtain the information"""
return self._config_reader
@property
def config_writer(self):
"""
:return: GitConfigParser compatible object able to write options for this remote.
:note:
You can only own one writer at a time - delete it to release the
configuration file and make it useable by others.
To assure consistent results, you should only query options through the
writer. Once you are done writing, you are free to use the config reader
once again."""
writer = self.repo.config_writer()
# clear our cache to assure we re-read the possibly changed configuration
try:
del(self._config_reader)
except AttributeError:
pass
#END handle exception
return SectionConstraint(writer, self._config_section_name()) | en | 0.834528 | # remote.py # Copyright (C) 2008, 2009 <NAME> (<EMAIL>) and contributors # # This module is part of GitPython and is released under # the BSD License: http://www.opensource.org/licenses/bsd-license.php # Module implementing a remote object allowing easy access to git remotes Wrapper for basic PushInfo to provide the previous interface which includes resolved objects instead of plain shas old_commit # object for the corresponding old_commit_sha Wrapper to restore the previous interface, resolving objects and wrapping references Provides easy read and write access to a git remote. Everything not part of this interface is considered an option for the current remote, allowing constructs like remote.pushurl to query the pushurl. NOTE: When querying configuration, the configuration accessor will be cached to speed up subsequent accesses. Initialize a remote instance :param repo: The repository we are a remote of :param name: the name of the remote, i.e. 'origin' # note: at some point we could just create a git command instance ourselves # but lets just be lazy for now #END assert git cmd #END verify interface # some oddity: on windows, python 2.5, it for some reason does not realize # that it has the config_writer property, but instead calls __getattr__ # which will not yield the expected results. 'pinging' the members # with a dir call creates the config_writer property that we require # ... bugs like these make me wonder wheter python really wants to be used # for production. It doesn't happen on linux though. # END windows special handling Allows to call this instance like remote.special( *args, **kwargs) to call git-remote special self.name # sometimes, probably due to a bug in python itself, we are being called # even though a slot of the same name exists # END handle exception :return: Iterator yielding Remote objects of the given repository # END for each configuration section :return: IterableList of RemoteReference objects. It is prefixed, allowing you to omit the remote path portion, i.e.:: remote.refs.master # yields RemoteReference('/refs/remotes/origin/master') :return: IterableList RemoteReference objects that do not have a corresponding head in the remote reference anymore as they have been deleted on the remote side, but are still available locally. The IterableList is prefixed, hence the 'origin' must be omitted. See 'refs' property for an example. # expecting # * [would prune] origin/new_branch # END for each line Create a new remote to the given repository :param repo: Repository instance that is to receive the new remote :param name: Desired name of the remote :param url: URL which corresponds to the remote's name :param kwargs: Additional arguments to be passed to the git-remote add command :return: New Remote instance :raise GitCommandError: in case an origin with that name already exists # add is an alias Remove the remote with the given name # alias Rename self to the given new_name :return: self # it contains cached values, section names are different now #END handle exception Fetch all changes for this remote, including new branches which will be forced in ( in case your local remote branch is not part the new remote branches ancestry anymore ). :param kwargs: Additional arguments passed to git-remote update :return: self Fetch the latest changes for this remote :param refspec: A "refspec" is used by fetch and push to describe the mapping between remote ref and local ref. They are combined with a colon in the format <src>:<dst>, preceded by an optional plus sign, +. For example: git fetch $URL refs/heads/master:refs/heads/origin means "grab the master branch head from the $URL and store it as my origin branch head". And git push $URL refs/heads/master:refs/heads/to-upstream means "publish my master branch head as to-upstream branch at $URL". See also git-push(1). Taken from the git manual :param progress: See 'push' method :param kwargs: Additional arguments to be passed to git-fetch :return: IterableList(FetchInfo, ...) list of FetchInfo instances providing detailed information about the fetch results :note: As fetch does not provide progress information to non-ttys, we cannot make it available here unfortunately as in the 'push' method. Pull changes from the given branch, being the same as a fetch followed by a merge of branch with your local branch. :param refspec: see 'fetch' method :param progress: see 'push' method :param kwargs: Additional arguments to be passed to git-pull :return: Please see 'fetch' method Push changes from source branch in refspec to target branch in refspec. :param refspec: see 'fetch' method :param progress: Instance of type RemoteProgress allowing the caller to receive progress information until the method returns. If None, progress information will be discarded :param kwargs: Additional arguments to be passed to git-push :return: IterableList(PushInfo, ...) iterable list of PushInfo instances, each one informing about an individual head which had been updated on the remote side. If the push contains rejected heads, these will have the PushInfo.ERROR bit set in their flags. If the operation fails completely, the length of the returned IterableList will be null. :return: GitConfigParser compatible object able to read options for only our remote. Hence you may simple type config.get("pushurl") to obtain the information :return: GitConfigParser compatible object able to write options for this remote. :note: You can only own one writer at a time - delete it to release the configuration file and make it useable by others. To assure consistent results, you should only query options through the writer. Once you are done writing, you are free to use the config reader once again. # clear our cache to assure we re-read the possibly changed configuration #END handle exception | 2.544036 | 3 |
score_map_method/activation_map.py | naver-ai/calm | 77 | 6620603 | """
CALM
Copyright (c) 2021-present NAVER Corp.
MIT license
"""
__all__ = ['activation_map']
def activation_map(model, images, targets, score_map_process,
superclass=None, **kwargs):
cams = model(images, targets, superclass, return_cam=score_map_process)
return cams
| """
CALM
Copyright (c) 2021-present NAVER Corp.
MIT license
"""
__all__ = ['activation_map']
def activation_map(model, images, targets, score_map_process,
superclass=None, **kwargs):
cams = model(images, targets, superclass, return_cam=score_map_process)
return cams
| en | 0.621563 | CALM Copyright (c) 2021-present NAVER Corp. MIT license | 2.071302 | 2 |
cogs/restricted.py | TrendingTechnology/tessarect-bot | 1 | 6620604 | import discord
from discord.ext import commands,tasks
import random
import requests
import json
import asyncio
import itertools
import io
from contextlib import redirect_stdout
mainaccid =900992402356043806
class Restricted(commands.Cog):
def __init__(self,bot):
self.bot=bot
##DANGEROUS-> "https://stackoverflow.com/questions/34385014/how-do-i-set-the-output-of-exec-to-variable-python"
##BUT RUNNING FROM SERVERS LIKE heroku TILL NOW HAVE NOT SHOWN ANY AFFECT ON THE CODING COMPUTER EVEN WITH OS MODULE CODES
##THE OUTPUT IS : "py"
##eval command->executes any python code and displays output(work in progress)
@commands.is_owner()
@commands.command(hidden=True)
async def servers(self,ctx):
activeservers = self.bot.guilds
for guild in activeservers:
name=str(guild.name)
description=str(guild.description)
owner=str(guild.owner)
_id = str(guild.id)
region=str(guild.region)
memcount=str(guild.member_count)
icon = str(guild.icon_url)
ver = str(ctx.guild.verification_level)
embed=discord.Embed(
title=name +" Server Information",
description=description,
color=discord.Color.blue()
)
embed.set_thumbnail(url=icon)
embed.add_field(name="Owner",value=owner,inline=True)
embed.add_field(name="Server Id",value=_id,inline=True)
embed.add_field(name="Region",value=region,inline=True)
embed.add_field(name="Member Count",value=memcount,inline=True)
embed.add_field(name="Verification Level",value=ver,inline=True)
await ctx.send(embed=embed)
print(guild.name)
@commands.is_owner()
@commands.command(hidden=True)
async def invservers(self,ctx):
invites = []
for guild in self.bot.guilds:
for c in guild.text_channels:
if c.permissions_for(guild.me).create_instant_invite: # make sure the bot can actually create an invite
invite = await c.create_invite()
invites.append(invite)
break
print(invites) # stop iterating over guild.text_channels, since you only need one invite per guild
@commands.is_owner()
@commands.command(hidden=True)
async def msgservers(self,ctx,*,text):
activeservers = self.bot.guilds
for guild in activeservers:
allowed=[]
for channel in guild.text_channels:
if channel.permissions_for(guild.me).send_messages and channel.permissions_for(guild.me).embed_links:
allowed.append(channel)
if len(allowed) >= 1:
to_post = allowed[0]
for channel in allowed:
if "general" in channel.name.lower():
to_post = channel
break
try:
await to_post.send(text)
await ctx.send("Sent message to Guild: "+guild.name+" Channel: "+to_post.name)
except Exception as e:
await ctx.send(e)
@commands.is_owner()
@commands.command(hidden=True)
async def msgserver(self,ctx):
def check(msg):
return msg.author == ctx.author and str(ctx.author.id) == mainaccid and msg.channel == ctx.channel
await ctx.send("Guild name:")
try:
guild = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Channel name:")
try:
channel = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Message:")
try:
msg = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Times:")
try:
times = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
activeservers = self.bot.guilds
for g in activeservers:
if g.name==guild.content:
for ch in g.channels:
if(ch.name == channel.content):
for i in range(int(times.content)):
try:
await ch.send(msg.content)
await ctx.send("Sent message")
except Exception as e:
await ctx.send(e)
def setup(bot):
bot.add_cog(Restricted(bot)) | import discord
from discord.ext import commands,tasks
import random
import requests
import json
import asyncio
import itertools
import io
from contextlib import redirect_stdout
mainaccid =900992402356043806
class Restricted(commands.Cog):
def __init__(self,bot):
self.bot=bot
##DANGEROUS-> "https://stackoverflow.com/questions/34385014/how-do-i-set-the-output-of-exec-to-variable-python"
##BUT RUNNING FROM SERVERS LIKE heroku TILL NOW HAVE NOT SHOWN ANY AFFECT ON THE CODING COMPUTER EVEN WITH OS MODULE CODES
##THE OUTPUT IS : "py"
##eval command->executes any python code and displays output(work in progress)
@commands.is_owner()
@commands.command(hidden=True)
async def servers(self,ctx):
activeservers = self.bot.guilds
for guild in activeservers:
name=str(guild.name)
description=str(guild.description)
owner=str(guild.owner)
_id = str(guild.id)
region=str(guild.region)
memcount=str(guild.member_count)
icon = str(guild.icon_url)
ver = str(ctx.guild.verification_level)
embed=discord.Embed(
title=name +" Server Information",
description=description,
color=discord.Color.blue()
)
embed.set_thumbnail(url=icon)
embed.add_field(name="Owner",value=owner,inline=True)
embed.add_field(name="Server Id",value=_id,inline=True)
embed.add_field(name="Region",value=region,inline=True)
embed.add_field(name="Member Count",value=memcount,inline=True)
embed.add_field(name="Verification Level",value=ver,inline=True)
await ctx.send(embed=embed)
print(guild.name)
@commands.is_owner()
@commands.command(hidden=True)
async def invservers(self,ctx):
invites = []
for guild in self.bot.guilds:
for c in guild.text_channels:
if c.permissions_for(guild.me).create_instant_invite: # make sure the bot can actually create an invite
invite = await c.create_invite()
invites.append(invite)
break
print(invites) # stop iterating over guild.text_channels, since you only need one invite per guild
@commands.is_owner()
@commands.command(hidden=True)
async def msgservers(self,ctx,*,text):
activeservers = self.bot.guilds
for guild in activeservers:
allowed=[]
for channel in guild.text_channels:
if channel.permissions_for(guild.me).send_messages and channel.permissions_for(guild.me).embed_links:
allowed.append(channel)
if len(allowed) >= 1:
to_post = allowed[0]
for channel in allowed:
if "general" in channel.name.lower():
to_post = channel
break
try:
await to_post.send(text)
await ctx.send("Sent message to Guild: "+guild.name+" Channel: "+to_post.name)
except Exception as e:
await ctx.send(e)
@commands.is_owner()
@commands.command(hidden=True)
async def msgserver(self,ctx):
def check(msg):
return msg.author == ctx.author and str(ctx.author.id) == mainaccid and msg.channel == ctx.channel
await ctx.send("Guild name:")
try:
guild = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Channel name:")
try:
channel = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Message:")
try:
msg = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
await ctx.send("Times:")
try:
times = await self.bot.wait_for("message", check=check , timeout=60)
except asyncio.TimeoutError:
await ctx.send("Sorry you took too long to respond!(waited for 60sec)")
return
activeservers = self.bot.guilds
for g in activeservers:
if g.name==guild.content:
for ch in g.channels:
if(ch.name == channel.content):
for i in range(int(times.content)):
try:
await ch.send(msg.content)
await ctx.send("Sent message")
except Exception as e:
await ctx.send(e)
def setup(bot):
bot.add_cog(Restricted(bot)) | en | 0.526278 | ##DANGEROUS-> "https://stackoverflow.com/questions/34385014/how-do-i-set-the-output-of-exec-to-variable-python" ##BUT RUNNING FROM SERVERS LIKE heroku TILL NOW HAVE NOT SHOWN ANY AFFECT ON THE CODING COMPUTER EVEN WITH OS MODULE CODES ##THE OUTPUT IS : "py" ##eval command->executes any python code and displays output(work in progress) # make sure the bot can actually create an invite # stop iterating over guild.text_channels, since you only need one invite per guild | 2.552223 | 3 |
rio/blueprints/api_1.py | soasme/rio | 0 | 6620605 | <reponame>soasme/rio
# -*- coding: utf-8 -*-
"""
rio.blueprints.api_1
~~~~~~~~~~~~~~~~~~~~~
"""
from flask import Blueprint
bp = Blueprint('api_1', __name__)
| # -*- coding: utf-8 -*-
"""
rio.blueprints.api_1
~~~~~~~~~~~~~~~~~~~~~
"""
from flask import Blueprint
bp = Blueprint('api_1', __name__) | en | 0.352277 | # -*- coding: utf-8 -*- rio.blueprints.api_1 ~~~~~~~~~~~~~~~~~~~~~ | 1.378232 | 1 |
src/ds/doubly_linkedlist.py | snandasena/python-oop | 0 | 6620606 | class Node:
def __init__(self, data, next=None, prev=None):
self.data = data
self.next = next
self.prev = prev
def __str__(self):
return ('(' + str(self.data) + ')')
class DoublyLinkedLint:
def __init__(self, r=None):
self.root = r
self.last = r
self.size = 0
def add(self, data):
if self.size == 0:
self.root = Node(data)
self.last = self.root
else:
new_node = Node(data, self.root)
self.root.prev = new_node
self.root = new_node
self.size += 1
def find(self, data):
curr = self.root
while curr is not None:
if curr.data == data:
return data
elif curr.next == None:
return False
else:
curr = curr.next
def remove(self, data):
curr = self.root
while curr is not None:
if curr.data == data:
if curr.prev is not None:
if curr.next is not None:
curr.prev.next = curr.next
curr.next.prev = curr.prev
else:
curr.next.prev = None
self.last = curr.prev
else:
self.root = curr.next
curr.next.prev = self.root
self.size += 1
return True
else:
curr = curr.next
return False
def print_list(self):
if self.root is None:
return
curr = self.root
print(curr, end='->')
while curr.next is not None:
curr = curr.next
print(curr, end='->')
print()
if __name__ == '__main__':
dll = DoublyLinkedLint()
for i in [5, 9, 3, 8, 9]:
dll.add(i)
print('size=', dll.size)
dll.print_list()
dll.remove(8)
dll.print_list()
| class Node:
def __init__(self, data, next=None, prev=None):
self.data = data
self.next = next
self.prev = prev
def __str__(self):
return ('(' + str(self.data) + ')')
class DoublyLinkedLint:
def __init__(self, r=None):
self.root = r
self.last = r
self.size = 0
def add(self, data):
if self.size == 0:
self.root = Node(data)
self.last = self.root
else:
new_node = Node(data, self.root)
self.root.prev = new_node
self.root = new_node
self.size += 1
def find(self, data):
curr = self.root
while curr is not None:
if curr.data == data:
return data
elif curr.next == None:
return False
else:
curr = curr.next
def remove(self, data):
curr = self.root
while curr is not None:
if curr.data == data:
if curr.prev is not None:
if curr.next is not None:
curr.prev.next = curr.next
curr.next.prev = curr.prev
else:
curr.next.prev = None
self.last = curr.prev
else:
self.root = curr.next
curr.next.prev = self.root
self.size += 1
return True
else:
curr = curr.next
return False
def print_list(self):
if self.root is None:
return
curr = self.root
print(curr, end='->')
while curr.next is not None:
curr = curr.next
print(curr, end='->')
print()
if __name__ == '__main__':
dll = DoublyLinkedLint()
for i in [5, 9, 3, 8, 9]:
dll.add(i)
print('size=', dll.size)
dll.print_list()
dll.remove(8)
dll.print_list()
| none | 1 | 3.5957 | 4 | |
src/utils/camerastreamer/camerastreamer.py | KeithAzzopardi1998/BFMC_Startup | 0 | 6620607 | <filename>src/utils/camerastreamer/camerastreamer.py
# Copyright (c) 2019, Bosch Engineering Center Cluj and BFMC organizers
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE
import socket
import struct
import time
import numpy as np
from multiprocessing import Process
from threading import Thread
import cv2
import os
from src.utils.templates.workerprocess import WorkerProcess
class CameraStreamer(WorkerProcess):
# ===================================== INIT =========================================
def __init__(self, inPs, outPs):
"""Process used for sending images over the network. UDP protocol is used. The
image is compressed before it is send.
Used for visualizing your raspicam from PC.
Parameters
----------
inPs : list(Pipe)
List of input pipes, only the first pipe is used to transfer the captured frames.
outPs : list(Pipe)
List of output pipes (not used at the moment)
"""
super(CameraStreamer,self).__init__( inPs, outPs)
self.serverIp = os.environ['IP_PC'] # PC ip
self.port = 2244 # com port
# ===================================== RUN ==========================================
def run(self):
"""Apply the initializing methods and start the threads.
"""
self._init_socket()
super(CameraStreamer,self).run()
# ===================================== INIT THREADS =================================
def _init_threads(self):
"""Initialize the sending thread.
"""
if self._blocker.is_set():
return
streamTh = Thread(name='StreamSending',target = self._send_thread, args= (self.inPs[0], ))
streamTh.daemon = True
self.threads.append(streamTh)
# ===================================== INIT SOCKET ==================================
def _init_socket(self):
"""Initialize the socket.
"""
self.client_socket = socket.socket()
self.connection = None
# Trying repeatedly to connect the camera receiver.
try:
while self.connection is None and not self._blocker.is_set():
try:
self.client_socket.connect((self.serverIp, self.port))
self.client_socket.setsockopt(socket.SOL_SOCKET,socket.SO_REUSEADDR,1)
self.connection = self.client_socket.makefile('wb')
except ConnectionRefusedError as error:
time.sleep(0.5)
pass
except KeyboardInterrupt:
self._blocker.set()
pass
# ===================================== SEND THREAD ==================================
def _send_thread(self, inP):
"""Sending the frames received thought the input pipe to remote client by using a socket.
Parameters
----------
inP : Pipe
Input pipe to read the frames from other process.
"""
encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 70]
print('Start streaming')
while True:
time.sleep(0.05)
try:
print("LOG: fetching image")
stamps, image = inP.recv()
print("LOG: image shape before processing",image.shape)
image=process_image(image)
print("LOG: image shape after processing",image.shape)
result, image = cv2.imencode('.jpg', image, encode_param)
data = image.tobytes()
size = len(data)
print("LOG: packaged image into packet of size %d ... going to transmit"%size)
self.connection.write(struct.pack("<L",size))
self.connection.write(data)
print("LOG: successfully transmitted frame")
except Exception as e:
print("CameraStreamer failed to stream images:",e,"\n")
# Reinitialize the socket for reconnecting to client.
self.connection = None
self._init_socket()
pass
import matplotlib.image as mpimg
import numpy as np
import cv2
def grayscale(img):
"""
Applies the Grayscale transform
This will return an image with only one color channel
but NOTE: to see the returned image as grayscale
(assuming your grayscaled image is called 'gray')
you should call plt.imshow(gray, cmap='gray')
If you read an image with cv2.imread() use BGR2GRAY
return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
"""
return cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
def canny(img, low_threshold, high_threshold):
"""Applies the Canny transform"""
return cv2.Canny(img, low_threshold, high_threshold)
def gaussian_blur(img, kernel_size):
"""Applies a Gaussian Noise kernel"""
return cv2.GaussianBlur(img, (kernel_size, kernel_size), 0)
def region_of_interest(img, vertices):
"""
Applies an image mask.
Only keeps the region of the image defined by the polygon
formed from `vertices`. The rest of the image is set to black.
`vertices` should be a numpy array of integer points.
"""
# Defining a blank mask to start with
mask = np.zeros_like(img)
# Defining a 3 channel or 1 channel color to fill the mask with depending on the input image
if len(img.shape) > 2:
channel_count = img.shape[2] # i.e. 3 or 4 depending on your image
ignore_mask_color = (255,) * channel_count
else:
ignore_mask_color = 255
# Filling pixels inside the polygon defined by "vertices" with the fill color
cv2.fillPoly(mask, vertices, ignore_mask_color)
# Returning the image only where mask pixels are nonzero
masked_image = cv2.bitwise_and(img, mask)
return masked_image
def draw_lines(img, lines, color=[255, 0, 0], thickness=2):
"""
NOTE: this is the function you might want to use as a starting point once you want to
average/extrapolate the line segments you detect to map out the full
extent of the lane (going from the result shown in raw-lines-example.mp4
to that shown in P1_example.mp4).
Think about things like separating line segments by their
slope ((y2-y1)/(x2-x1)) to decide which segments are part of the left
line vs. the right line. Then, you can average the position of each of
the lines and extrapolate to the top and bottom of the lane.
This function draws `lines` with `color` and `thickness`.
Lines are drawn on the image inplace (mutates the image).
If you want to make the lines semi-transparent, think about combining
this function with the weighted_img() function below
"""
for line in lines:
for x1,y1,x2,y2 in line:
cv2.line(img, (x1, y1), (x2, y2), color, thickness)
def hough_lines(img, rho, theta, threshold, min_line_len, max_line_gap):
"""
`img` should be the output of a Canny transform.
Returns an image with hough lines drawn.
"""
lines = cv2.HoughLinesP(img, rho, theta, threshold, np.array([]), minLineLength=min_line_len, maxLineGap=max_line_gap)
line_img = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)
draw_lines(line_img, lines)
return line_img
# Python 3 has support for cool math symbols.
def weighted_img(img, initial_img, α=0.8, β=1., γ=0.):
"""
`img` is the output of the hough_lines(), An image with lines drawn on it.
Should be a blank image (all black) with lines drawn on it.
`initial_img` should be the image before any processing.
The result image is computed as follows:
initial_img * α + img * β + γ
NOTE: initial_img and img must be the same shape!
"""
return cv2.addWeighted(initial_img, α, img, β, γ)
def process_image(img):
#read_image = mpimg.imread(img)
image = np.copy(img)
gray_image = grayscale(image)
blur_gray = gaussian_blur(gray_image, kernel_size=5)
edges = canny(blur_gray, low_threshold=90, high_threshold=180)
imshape = image.shape
vertices = np.array([[(0, imshape[0]), (480, 300), (480, 300), (imshape[1], imshape[0])]], dtype=np.int32)
masked_edges = region_of_interest(edges, vertices)
line_image = hough_lines(masked_edges, rho=1, theta=np.pi/180, threshold=50, min_line_len=25, max_line_gap=200)
lines_edges = weighted_img(line_image, image, α=0.8, β=1., γ=0.)
return lines_edges | <filename>src/utils/camerastreamer/camerastreamer.py
# Copyright (c) 2019, Bosch Engineering Center Cluj and BFMC organizers
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE
import socket
import struct
import time
import numpy as np
from multiprocessing import Process
from threading import Thread
import cv2
import os
from src.utils.templates.workerprocess import WorkerProcess
class CameraStreamer(WorkerProcess):
# ===================================== INIT =========================================
def __init__(self, inPs, outPs):
"""Process used for sending images over the network. UDP protocol is used. The
image is compressed before it is send.
Used for visualizing your raspicam from PC.
Parameters
----------
inPs : list(Pipe)
List of input pipes, only the first pipe is used to transfer the captured frames.
outPs : list(Pipe)
List of output pipes (not used at the moment)
"""
super(CameraStreamer,self).__init__( inPs, outPs)
self.serverIp = os.environ['IP_PC'] # PC ip
self.port = 2244 # com port
# ===================================== RUN ==========================================
def run(self):
"""Apply the initializing methods and start the threads.
"""
self._init_socket()
super(CameraStreamer,self).run()
# ===================================== INIT THREADS =================================
def _init_threads(self):
"""Initialize the sending thread.
"""
if self._blocker.is_set():
return
streamTh = Thread(name='StreamSending',target = self._send_thread, args= (self.inPs[0], ))
streamTh.daemon = True
self.threads.append(streamTh)
# ===================================== INIT SOCKET ==================================
def _init_socket(self):
"""Initialize the socket.
"""
self.client_socket = socket.socket()
self.connection = None
# Trying repeatedly to connect the camera receiver.
try:
while self.connection is None and not self._blocker.is_set():
try:
self.client_socket.connect((self.serverIp, self.port))
self.client_socket.setsockopt(socket.SOL_SOCKET,socket.SO_REUSEADDR,1)
self.connection = self.client_socket.makefile('wb')
except ConnectionRefusedError as error:
time.sleep(0.5)
pass
except KeyboardInterrupt:
self._blocker.set()
pass
# ===================================== SEND THREAD ==================================
def _send_thread(self, inP):
"""Sending the frames received thought the input pipe to remote client by using a socket.
Parameters
----------
inP : Pipe
Input pipe to read the frames from other process.
"""
encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), 70]
print('Start streaming')
while True:
time.sleep(0.05)
try:
print("LOG: fetching image")
stamps, image = inP.recv()
print("LOG: image shape before processing",image.shape)
image=process_image(image)
print("LOG: image shape after processing",image.shape)
result, image = cv2.imencode('.jpg', image, encode_param)
data = image.tobytes()
size = len(data)
print("LOG: packaged image into packet of size %d ... going to transmit"%size)
self.connection.write(struct.pack("<L",size))
self.connection.write(data)
print("LOG: successfully transmitted frame")
except Exception as e:
print("CameraStreamer failed to stream images:",e,"\n")
# Reinitialize the socket for reconnecting to client.
self.connection = None
self._init_socket()
pass
import matplotlib.image as mpimg
import numpy as np
import cv2
def grayscale(img):
"""
Applies the Grayscale transform
This will return an image with only one color channel
but NOTE: to see the returned image as grayscale
(assuming your grayscaled image is called 'gray')
you should call plt.imshow(gray, cmap='gray')
If you read an image with cv2.imread() use BGR2GRAY
return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
"""
return cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
def canny(img, low_threshold, high_threshold):
"""Applies the Canny transform"""
return cv2.Canny(img, low_threshold, high_threshold)
def gaussian_blur(img, kernel_size):
"""Applies a Gaussian Noise kernel"""
return cv2.GaussianBlur(img, (kernel_size, kernel_size), 0)
def region_of_interest(img, vertices):
"""
Applies an image mask.
Only keeps the region of the image defined by the polygon
formed from `vertices`. The rest of the image is set to black.
`vertices` should be a numpy array of integer points.
"""
# Defining a blank mask to start with
mask = np.zeros_like(img)
# Defining a 3 channel or 1 channel color to fill the mask with depending on the input image
if len(img.shape) > 2:
channel_count = img.shape[2] # i.e. 3 or 4 depending on your image
ignore_mask_color = (255,) * channel_count
else:
ignore_mask_color = 255
# Filling pixels inside the polygon defined by "vertices" with the fill color
cv2.fillPoly(mask, vertices, ignore_mask_color)
# Returning the image only where mask pixels are nonzero
masked_image = cv2.bitwise_and(img, mask)
return masked_image
def draw_lines(img, lines, color=[255, 0, 0], thickness=2):
"""
NOTE: this is the function you might want to use as a starting point once you want to
average/extrapolate the line segments you detect to map out the full
extent of the lane (going from the result shown in raw-lines-example.mp4
to that shown in P1_example.mp4).
Think about things like separating line segments by their
slope ((y2-y1)/(x2-x1)) to decide which segments are part of the left
line vs. the right line. Then, you can average the position of each of
the lines and extrapolate to the top and bottom of the lane.
This function draws `lines` with `color` and `thickness`.
Lines are drawn on the image inplace (mutates the image).
If you want to make the lines semi-transparent, think about combining
this function with the weighted_img() function below
"""
for line in lines:
for x1,y1,x2,y2 in line:
cv2.line(img, (x1, y1), (x2, y2), color, thickness)
def hough_lines(img, rho, theta, threshold, min_line_len, max_line_gap):
"""
`img` should be the output of a Canny transform.
Returns an image with hough lines drawn.
"""
lines = cv2.HoughLinesP(img, rho, theta, threshold, np.array([]), minLineLength=min_line_len, maxLineGap=max_line_gap)
line_img = np.zeros((img.shape[0], img.shape[1], 3), dtype=np.uint8)
draw_lines(line_img, lines)
return line_img
# Python 3 has support for cool math symbols.
def weighted_img(img, initial_img, α=0.8, β=1., γ=0.):
"""
`img` is the output of the hough_lines(), An image with lines drawn on it.
Should be a blank image (all black) with lines drawn on it.
`initial_img` should be the image before any processing.
The result image is computed as follows:
initial_img * α + img * β + γ
NOTE: initial_img and img must be the same shape!
"""
return cv2.addWeighted(initial_img, α, img, β, γ)
def process_image(img):
#read_image = mpimg.imread(img)
image = np.copy(img)
gray_image = grayscale(image)
blur_gray = gaussian_blur(gray_image, kernel_size=5)
edges = canny(blur_gray, low_threshold=90, high_threshold=180)
imshape = image.shape
vertices = np.array([[(0, imshape[0]), (480, 300), (480, 300), (imshape[1], imshape[0])]], dtype=np.int32)
masked_edges = region_of_interest(edges, vertices)
line_image = hough_lines(masked_edges, rho=1, theta=np.pi/180, threshold=50, min_line_len=25, max_line_gap=200)
lines_edges = weighted_img(line_image, image, α=0.8, β=1., γ=0.)
return lines_edges | en | 0.802447 | # Copyright (c) 2019, Bosch Engineering Center Cluj and BFMC organizers # All rights reserved. # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # 3. Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE # ===================================== INIT ========================================= Process used for sending images over the network. UDP protocol is used. The image is compressed before it is send. Used for visualizing your raspicam from PC. Parameters ---------- inPs : list(Pipe) List of input pipes, only the first pipe is used to transfer the captured frames. outPs : list(Pipe) List of output pipes (not used at the moment) # PC ip # com port # ===================================== RUN ========================================== Apply the initializing methods and start the threads. # ===================================== INIT THREADS ================================= Initialize the sending thread. # ===================================== INIT SOCKET ================================== Initialize the socket. # Trying repeatedly to connect the camera receiver. # ===================================== SEND THREAD ================================== Sending the frames received thought the input pipe to remote client by using a socket. Parameters ---------- inP : Pipe Input pipe to read the frames from other process. # Reinitialize the socket for reconnecting to client. Applies the Grayscale transform This will return an image with only one color channel but NOTE: to see the returned image as grayscale (assuming your grayscaled image is called 'gray') you should call plt.imshow(gray, cmap='gray') If you read an image with cv2.imread() use BGR2GRAY return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) Applies the Canny transform Applies a Gaussian Noise kernel Applies an image mask. Only keeps the region of the image defined by the polygon formed from `vertices`. The rest of the image is set to black. `vertices` should be a numpy array of integer points. # Defining a blank mask to start with # Defining a 3 channel or 1 channel color to fill the mask with depending on the input image # i.e. 3 or 4 depending on your image # Filling pixels inside the polygon defined by "vertices" with the fill color # Returning the image only where mask pixels are nonzero NOTE: this is the function you might want to use as a starting point once you want to average/extrapolate the line segments you detect to map out the full extent of the lane (going from the result shown in raw-lines-example.mp4 to that shown in P1_example.mp4). Think about things like separating line segments by their slope ((y2-y1)/(x2-x1)) to decide which segments are part of the left line vs. the right line. Then, you can average the position of each of the lines and extrapolate to the top and bottom of the lane. This function draws `lines` with `color` and `thickness`. Lines are drawn on the image inplace (mutates the image). If you want to make the lines semi-transparent, think about combining this function with the weighted_img() function below `img` should be the output of a Canny transform. Returns an image with hough lines drawn. # Python 3 has support for cool math symbols. `img` is the output of the hough_lines(), An image with lines drawn on it. Should be a blank image (all black) with lines drawn on it. `initial_img` should be the image before any processing. The result image is computed as follows: initial_img * α + img * β + γ NOTE: initial_img and img must be the same shape! #read_image = mpimg.imread(img) | 1.60349 | 2 |
development-resources/investigations/audio_format.py | CameronJRAllan/eTree-Browser | 1 | 6620608 | <filename>development-resources/investigations/audio_format.py
import sys
from SPARQLWrapper import SPARQLWrapper, JSON, POSTDIRECTLY
import cache
import statistics as s
class AudioFormat():
def __init__(self):
self.sparql = SPARQLWrapper("http://etree.linkedmusic.org/sparql")
self.sparql.setReturnFormat(JSON)
self.sparql.setMethod("POST")
performances = cache.load('list_all_performances')
# performances = self.get_all_performances()
# cache.save(performances, 'list_all_performances')
print('Got perm')
self.examine_tracklists(performances)
def examine_tracklists(self, performances):
count = {'mp3': 0, 'flac24': 0, 'flac16': 0, 'mp3_vbr': 0, 'shn' : 0, 'ogg': 0, 'wav' : 0}
numSingleFormat = 0
countUnique = {'mp3': 0, 'flac24': 0, 'flac16': 0, 'mp3_vbr': 0, 'shn' : 0, 'ogg': 0, 'wav' : 0}
numFormatsFound = []
for single in performances['results']['bindings']: # [:40]
tracklist = self.get_tracklist(single['label']['value'])
print(single['label']['value'])
formatsFound = []
for item in tracklist['results']['bindings']:
extension = item['audio']['value'][item['audio']['value'].rfind('.') + 1:]
if 'mp3' not in extension and 'flac' not in extension:
formatsFound.append(extension)
else:
if 'mp3' in extension:
formatsFound.append(self.subtype_mp3(item['audio']['value']))
if 'flac' in extension:
formatsFound.append(self.subtype_flac(item['audio']['value']))
if len(list(set(formatsFound))) == 1:
numSingleFormat += 1
countUnique[formatsFound[0]] += 1
numFormatsFound.append(len(list(set(formatsFound))))
for format in list(set(formatsFound)):
count[format] += 1
for k in count.keys():
print(str(k) + ': ' + str(count[k]))
print('\n\nUnique count: ' + str(numSingleFormat))
for k in countUnique.keys():
print(str(k) + ': ' + str(countUnique[k]))
print(s.mean(numFormatsFound))
def subtype_mp3(self, url):
final_7 = url[url.rfind('.') - 3:]
if 'vbr' in final_7.lower():
return 'mp3_vbr'
if '64kb' in final_7.lower():
return 'mp3_64kb'
else:
return 'mp3'
def subtype_flac(self, url):
filename = url[url.rfind('/') + 1:]
if 'flac24' in url.lower():
return 'flac24'
else:
return 'flac16'
def get_all_performances(self):
self.sparql.setQuery("""
PREFIX etree:<http://etree.linkedmusic.org/vocab/>
PREFIX mo:<http://purl.org/ontology/mo/>
PREFIX event:<http://purl.org/NET/c4dm/event.owl#>
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?performer ?name ?label ?place WHERE
{
?art skos:prefLabel ?label.
?art event:place ?location.
?location etree:location ?place.
?performer foaf:name ?name.
?art mo:performer ?performer.
} GROUP BY (?name) LIMIT 2
""")
return self.sparql.query().convert()
def get_tracklist(self, label):
self.sparql.setQuery("""
PREFIX etree:<http://etree.linkedmusic.org/vocab/>
PREFIX mo:<http://purl.org/ontology/mo/>
PREFIX event:<http://purl.org/NET/c4dm/event.owl#>
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?audio ?label ?num {{
?perf event:hasSubEvent ?tracklist.
?tracklist skos:prefLabel ?label.
?tracklist etree:number ?num.
?tracklist etree:audio ?audio.
?perf rdf:type mo:Performance.
?perf skos:prefLabel "{0}".
}} GROUP BY ?label ?audio ?num ORDER BY ?num
""".format(label))
return self.sparql.query().convert()
if __name__ == '__main__':
instance = AudioFormat() | <filename>development-resources/investigations/audio_format.py
import sys
from SPARQLWrapper import SPARQLWrapper, JSON, POSTDIRECTLY
import cache
import statistics as s
class AudioFormat():
def __init__(self):
self.sparql = SPARQLWrapper("http://etree.linkedmusic.org/sparql")
self.sparql.setReturnFormat(JSON)
self.sparql.setMethod("POST")
performances = cache.load('list_all_performances')
# performances = self.get_all_performances()
# cache.save(performances, 'list_all_performances')
print('Got perm')
self.examine_tracklists(performances)
def examine_tracklists(self, performances):
count = {'mp3': 0, 'flac24': 0, 'flac16': 0, 'mp3_vbr': 0, 'shn' : 0, 'ogg': 0, 'wav' : 0}
numSingleFormat = 0
countUnique = {'mp3': 0, 'flac24': 0, 'flac16': 0, 'mp3_vbr': 0, 'shn' : 0, 'ogg': 0, 'wav' : 0}
numFormatsFound = []
for single in performances['results']['bindings']: # [:40]
tracklist = self.get_tracklist(single['label']['value'])
print(single['label']['value'])
formatsFound = []
for item in tracklist['results']['bindings']:
extension = item['audio']['value'][item['audio']['value'].rfind('.') + 1:]
if 'mp3' not in extension and 'flac' not in extension:
formatsFound.append(extension)
else:
if 'mp3' in extension:
formatsFound.append(self.subtype_mp3(item['audio']['value']))
if 'flac' in extension:
formatsFound.append(self.subtype_flac(item['audio']['value']))
if len(list(set(formatsFound))) == 1:
numSingleFormat += 1
countUnique[formatsFound[0]] += 1
numFormatsFound.append(len(list(set(formatsFound))))
for format in list(set(formatsFound)):
count[format] += 1
for k in count.keys():
print(str(k) + ': ' + str(count[k]))
print('\n\nUnique count: ' + str(numSingleFormat))
for k in countUnique.keys():
print(str(k) + ': ' + str(countUnique[k]))
print(s.mean(numFormatsFound))
def subtype_mp3(self, url):
final_7 = url[url.rfind('.') - 3:]
if 'vbr' in final_7.lower():
return 'mp3_vbr'
if '64kb' in final_7.lower():
return 'mp3_64kb'
else:
return 'mp3'
def subtype_flac(self, url):
filename = url[url.rfind('/') + 1:]
if 'flac24' in url.lower():
return 'flac24'
else:
return 'flac16'
def get_all_performances(self):
self.sparql.setQuery("""
PREFIX etree:<http://etree.linkedmusic.org/vocab/>
PREFIX mo:<http://purl.org/ontology/mo/>
PREFIX event:<http://purl.org/NET/c4dm/event.owl#>
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?performer ?name ?label ?place WHERE
{
?art skos:prefLabel ?label.
?art event:place ?location.
?location etree:location ?place.
?performer foaf:name ?name.
?art mo:performer ?performer.
} GROUP BY (?name) LIMIT 2
""")
return self.sparql.query().convert()
def get_tracklist(self, label):
self.sparql.setQuery("""
PREFIX etree:<http://etree.linkedmusic.org/vocab/>
PREFIX mo:<http://purl.org/ontology/mo/>
PREFIX event:<http://purl.org/NET/c4dm/event.owl#>
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
SELECT DISTINCT ?audio ?label ?num {{
?perf event:hasSubEvent ?tracklist.
?tracklist skos:prefLabel ?label.
?tracklist etree:number ?num.
?tracklist etree:audio ?audio.
?perf rdf:type mo:Performance.
?perf skos:prefLabel "{0}".
}} GROUP BY ?label ?audio ?num ORDER BY ?num
""".format(label))
return self.sparql.query().convert()
if __name__ == '__main__':
instance = AudioFormat() | en | 0.267127 | # performances = self.get_all_performances() # cache.save(performances, 'list_all_performances') # [:40] PREFIX etree:<http://etree.linkedmusic.org/vocab/> PREFIX mo:<http://purl.org/ontology/mo/> PREFIX event:<http://purl.org/NET/c4dm/event.owl#> PREFIX skos:<http://www.w3.org/2004/02/skos/core#> PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> SELECT DISTINCT ?performer ?name ?label ?place WHERE { ?art skos:prefLabel ?label. ?art event:place ?location. ?location etree:location ?place. ?performer foaf:name ?name. ?art mo:performer ?performer. } GROUP BY (?name) LIMIT 2 PREFIX etree:<http://etree.linkedmusic.org/vocab/> PREFIX mo:<http://purl.org/ontology/mo/> PREFIX event:<http://purl.org/NET/c4dm/event.owl#> PREFIX skos:<http://www.w3.org/2004/02/skos/core#> PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> SELECT DISTINCT ?audio ?label ?num {{ ?perf event:hasSubEvent ?tracklist. ?tracklist skos:prefLabel ?label. ?tracklist etree:number ?num. ?tracklist etree:audio ?audio. ?perf rdf:type mo:Performance. ?perf skos:prefLabel "{0}". }} GROUP BY ?label ?audio ?num ORDER BY ?num | 2.405538 | 2 |
fingo/scaling.py | aquatix/fingo | 0 | 6620609 | # encoding: utf-8
from __future__ import absolute_import
import logging
import os
from PIL import Image as PILImage, ImageFile as PILImageFile, ExifTags
from datetime import datetime
import exifread
import imagehash
import json
import pytz
import requests
try:
DEBUG = settings.DEBUG
except NameError:
DEBUG = True
#DEBUG = False
logger = logging.getLogger('fingo')
logger.setLevel(logging.DEBUG)
lh = logging.StreamHandler()
if DEBUG:
lh.setLevel(logging.DEBUG)
else:
lh.setLevel(logging.ERROR)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
lh.setFormatter(formatter)
logger.addHandler(lh)
def scale_image(image_id, destination_dir, width, height, crop=False):
"""
Create scaled versions of the Image with image_id
"""
image = Image.objects.get(pk=image_id)
if not image.image_hash:
logger.info('No hash found for Image with pk %d', image.pk)
return
filename_base = os.path.join(destination_dir, image.image_hash[:2], image.image_hash)
util.ensure_dir_exists(filename_base)
variant = '_{}-{}.{}'.format(width, height, image.file_ext)
if os.path.isfile(filename_base + variant):
#logger.debug('Skipping resize for existing %s%s', filename_base, variant)
return
logger.info('resizing into %s', filename_base + variant)
# TODO: be more clever with the config
if width == 0:
raise Exception('width can not be zero')
if height == 0:
raise Exception('height can not be zero')
try:
im = PILImage.open(image.get_filepath())
im.thumbnail((width, height))
if image.file_ext == 'jpg' or image.file_ext == 'jpeg':
if width >= settings.EXIF_COPY_THRESHOLD or height >= settings.EXIF_COPY_THRESHOLD:
# If variant is larger than the set threshold, copy EXIF tags
# Smaller variants effectively get EXIF stripped so resulting files are smaller
# (good for thumbnails)
try:
exif = im.info['exif']
im.save(filename_base + variant, 'JPEG', exif=exif)
except KeyError:
# No EXIF found, save normally
im.save(filename_base + variant, 'JPEG')
else:
im.save(filename_base + variant, 'JPEG')
elif image.file_ext == 'png':
im.save(filename_base + variant, 'PNG')
except IOError:
logger.info('Cannot create %dx%d variant for %s', width, height, image)
def update_scaled_images(collection):
"""
Iterate through the images in the Collection and generate resized versions of images
that don't have those yet
"""
images = collection.images()
variants = PhotoSize.objects.all()
if len(variants) == 0:
logger.info('No size variants defined, configure some PhotoSizes')
return
for image in images:
for variant in variants:
scale_image(image.pk, collection.archive_dir, variant.width, variant.height, variant.crop_to_fit)
| # encoding: utf-8
from __future__ import absolute_import
import logging
import os
from PIL import Image as PILImage, ImageFile as PILImageFile, ExifTags
from datetime import datetime
import exifread
import imagehash
import json
import pytz
import requests
try:
DEBUG = settings.DEBUG
except NameError:
DEBUG = True
#DEBUG = False
logger = logging.getLogger('fingo')
logger.setLevel(logging.DEBUG)
lh = logging.StreamHandler()
if DEBUG:
lh.setLevel(logging.DEBUG)
else:
lh.setLevel(logging.ERROR)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
lh.setFormatter(formatter)
logger.addHandler(lh)
def scale_image(image_id, destination_dir, width, height, crop=False):
"""
Create scaled versions of the Image with image_id
"""
image = Image.objects.get(pk=image_id)
if not image.image_hash:
logger.info('No hash found for Image with pk %d', image.pk)
return
filename_base = os.path.join(destination_dir, image.image_hash[:2], image.image_hash)
util.ensure_dir_exists(filename_base)
variant = '_{}-{}.{}'.format(width, height, image.file_ext)
if os.path.isfile(filename_base + variant):
#logger.debug('Skipping resize for existing %s%s', filename_base, variant)
return
logger.info('resizing into %s', filename_base + variant)
# TODO: be more clever with the config
if width == 0:
raise Exception('width can not be zero')
if height == 0:
raise Exception('height can not be zero')
try:
im = PILImage.open(image.get_filepath())
im.thumbnail((width, height))
if image.file_ext == 'jpg' or image.file_ext == 'jpeg':
if width >= settings.EXIF_COPY_THRESHOLD or height >= settings.EXIF_COPY_THRESHOLD:
# If variant is larger than the set threshold, copy EXIF tags
# Smaller variants effectively get EXIF stripped so resulting files are smaller
# (good for thumbnails)
try:
exif = im.info['exif']
im.save(filename_base + variant, 'JPEG', exif=exif)
except KeyError:
# No EXIF found, save normally
im.save(filename_base + variant, 'JPEG')
else:
im.save(filename_base + variant, 'JPEG')
elif image.file_ext == 'png':
im.save(filename_base + variant, 'PNG')
except IOError:
logger.info('Cannot create %dx%d variant for %s', width, height, image)
def update_scaled_images(collection):
"""
Iterate through the images in the Collection and generate resized versions of images
that don't have those yet
"""
images = collection.images()
variants = PhotoSize.objects.all()
if len(variants) == 0:
logger.info('No size variants defined, configure some PhotoSizes')
return
for image in images:
for variant in variants:
scale_image(image.pk, collection.archive_dir, variant.width, variant.height, variant.crop_to_fit)
| en | 0.800171 | # encoding: utf-8 #DEBUG = False Create scaled versions of the Image with image_id #logger.debug('Skipping resize for existing %s%s', filename_base, variant) # TODO: be more clever with the config # If variant is larger than the set threshold, copy EXIF tags # Smaller variants effectively get EXIF stripped so resulting files are smaller # (good for thumbnails) # No EXIF found, save normally Iterate through the images in the Collection and generate resized versions of images that don't have those yet | 2.536353 | 3 |
python2.7/tests.py | PereBal/Komparator | 0 | 6620610 | <reponame>PereBal/Komparator<filename>python2.7/tests.py<gh_stars>0
# TODO
# model: (int, 1) -> funciona com toca. Les tuples son especials x)
# faltaria afegir un parseig del model
import unittest
from dictcompy import (DictComPy, Opt, Eq, Excl, In, Like, Date, Or_None,
Or_Empty)
MODELS = {
'int': [{'a': int}],
'float': [{'a': float}],
'complex': [{'a': complex}],
'bool': [{'a': bool}],
'str': [{'a': str}],
'list': [{'a': list}, {'a': []}, {'a': (list, [])}, {'a': [int]},
{'a': [int, str, bool]}],
'tuple': [{'a': tuple}, {'a': (tuple, (int,))},
{'a': (tuple, (int,str,bool))}],
'dict': [],
}
class TestDictComPy(unittest.TestCase):
def test_plain_int(self):
dcp = DictComPy(model=MODELS['int'][0])
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': 1}))
self.assertTrue(dcp.match(expr={'a': 0}))
def test_plain_float(self):
dcp = DictComPy(model=MODELS['float'][0])
self.assertFalse(dcp.match(expr={'b': 1.0}))
self.assertFalse(dcp.match(expr={'a': 0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': 1.0}))
def test_plain_complex(self):
dcp = DictComPy(model=MODELS['complex'][0])
c = complex(1, 2)
self.assertFalse(dcp.match(expr={'b': c}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': c}))
def test_plain_bool(self):
dcp = DictComPy(model=MODELS['bool'][0])
self.assertFalse(dcp.match(expr={'b': True}))
self.assertFalse(dcp.match(expr={'a': 0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': True}))
self.assertTrue(dcp.match(expr={'a': False}))
def test_plain_string(self):
dcp = DictComPy(model=MODELS['str'][0])
self.assertFalse(dcp.match(expr={'b': u'a'}))
self.assertFalse(dcp.match(expr={'a': 23}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertTrue(dcp.match(expr={'a': 'a'}))
self.assertTrue(dcp.match(expr={'a': u'a'}))
self.assertTrue(dcp.match(expr={'a': u''}))
self.assertTrue(dcp.match(expr={'a': ''}))
def test_plain_list(self):
dcp = DictComPy(model=MODELS['list'][0])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': []}))
self.assertTrue(dcp.match(expr={'a': [1]}))
self.assertTrue(dcp.match(expr={'a': [1, '1021', True]}))
dcp = DictComPy(model=MODELS['list'][1])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': []}))
dcp = DictComPy(model=MODELS['list'][2])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': []}))
dcp = DictComPy(model=MODELS['list'][3])
self.assertFalse(dcp.match(expr={'b': [1]}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': [1]}))
self.assertTrue(dcp.match(expr={'a': [1, 2, 3]}))
dcp = DictComPy(model=MODELS['list'][4])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True, 1.0]}))
self.assertTrue(dcp.match(expr={'a': [1, '1021', True]}))
def test_plain_tuple(self):
dcp = DictComPy(model=MODELS['tuple'][0])
self.assertFalse(dcp.match(expr={'b': ()}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)})) # 1, <-- common mistake
self.assertTrue(dcp.match(expr={'a': (1, '1021', True)}))
dcp = DictComPy(model=MODELS['tuple'][1]) # ',' <--
self.assertFalse(dcp.match(expr={'b': (1,)}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': ()}))
self.assertFalse(dcp.match(expr={'a': (1, '1021', True)}))
self.assertFalse(dcp.match(expr={'a': ('',)}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
self.assertTrue(dcp.match(expr={'a': (1, 2, 3)}))
dcp = DictComPy(model=MODELS['tuple'][2]) # ',' <--
self.assertFalse(dcp.match(expr={'b': (1,)}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': ()}))
self.assertFalse(dcp.match(expr={'a': (1,)}))
self.assertFalse(dcp.match(expr={'a': (1, 2, 3)}))
self.assertFalse(dcp.match(expr={'a': (1, '1021', True, 1.0)}))
self.assertTrue(dcp.match(expr={'a': (1, '1021', True)}))
def test_nested_int(self):
dcp = DictComPy({'a': {'b': int}})
self.assertFalse(dcp.match(expr={'b': {'b': 1}}))
self.assertFalse(dcp.match(expr={'a': {'a': 1}}))
self.assertFalse(dcp.match(expr={'a': {'b': ''}}))
self.assertTrue(dcp.match(expr={'a': {'b': 1}}))
def test_In(self):
dcp = DictComPy({'a': (In, range(0,5,2))})
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 10}))
self.assertTrue(dcp.match(expr={'a': 2}))
def test_Like(self):
dcp = DictComPy({'a': (Like, '\d,\w+')})
self.assertFalse(dcp.match(expr={'a': '1,'}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': '10'}))
self.assertTrue(dcp.match(expr={'a': '1,0102dsada_dede'}))
def test_Date(self):
dcp = DictComPy({'a': (Date, '%Y-%d-%m')})
self.assertFalse(dcp.match(expr={'a': '2015-02-31'}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': '2015-32-01'}))
self.assertTrue(dcp.match(expr={'a': '2015-30-01'}))
def test_Excl(self):
dcp = DictComPy({'a': (Excl, ('1', '2'), {'1': int, '2': str})})
self.assertFalse(dcp.match(expr={'a': {'1': 's'}}))
self.assertFalse(dcp.match(expr={'a': {'2': 1}}))
self.assertFalse(dcp.match(expr={'a': {'1': 1, '2': 's'}}))
self.assertTrue(dcp.match(expr={'a': {'1': 1}}))
self.assertTrue(dcp.match(expr={'a': {'2': 's'}}))
def test_Opt(self):
dcp = DictComPy({'a': (Opt, int)})
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 's'}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertTrue(dcp.match(expr={'a': 1}))
self.assertTrue(dcp.match(expr={'b': 1}))
def test_Eq(self):
dcp = DictComPy({'a': (Eq, 3)})
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': 4}))
self.assertTrue(dcp.match(expr={'a': 3}))
dcp = DictComPy({'a': (Eq, dict)})
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': list}))
self.assertTrue(dcp.match(expr={'a': dict}))
def test_Or_None(self):
dcp = DictComPy({'a': (Or_None, int)})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertTrue(dcp.match(expr={'a': None}))
self.assertTrue(dcp.match(expr={'a': 1}))
dcp = DictComPy({'a': (Or_None, (tuple, int))})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
def test_Or_Empty(self):
dcp = DictComPy({'a': (Or_Empty, {'b': int})})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': {'b': 1}}))
dcp = DictComPy({'a': (Or_Empty, [int])})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ['df']}))
self.assertTrue(dcp.match(expr={'a': []}))
self.assertTrue(dcp.match(expr={'a': [1]}))
""" Failing
dcp = DictComPy({'a': (Or_Empty, (tuple, int))})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
"""
if __name__ == '__main__':
unittest.main()
| # TODO
# model: (int, 1) -> funciona com toca. Les tuples son especials x)
# faltaria afegir un parseig del model
import unittest
from dictcompy import (DictComPy, Opt, Eq, Excl, In, Like, Date, Or_None,
Or_Empty)
MODELS = {
'int': [{'a': int}],
'float': [{'a': float}],
'complex': [{'a': complex}],
'bool': [{'a': bool}],
'str': [{'a': str}],
'list': [{'a': list}, {'a': []}, {'a': (list, [])}, {'a': [int]},
{'a': [int, str, bool]}],
'tuple': [{'a': tuple}, {'a': (tuple, (int,))},
{'a': (tuple, (int,str,bool))}],
'dict': [],
}
class TestDictComPy(unittest.TestCase):
def test_plain_int(self):
dcp = DictComPy(model=MODELS['int'][0])
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': 1}))
self.assertTrue(dcp.match(expr={'a': 0}))
def test_plain_float(self):
dcp = DictComPy(model=MODELS['float'][0])
self.assertFalse(dcp.match(expr={'b': 1.0}))
self.assertFalse(dcp.match(expr={'a': 0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': 1.0}))
def test_plain_complex(self):
dcp = DictComPy(model=MODELS['complex'][0])
c = complex(1, 2)
self.assertFalse(dcp.match(expr={'b': c}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertTrue(dcp.match(expr={'a': c}))
def test_plain_bool(self):
dcp = DictComPy(model=MODELS['bool'][0])
self.assertFalse(dcp.match(expr={'b': True}))
self.assertFalse(dcp.match(expr={'a': 0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 'as'}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': True}))
self.assertTrue(dcp.match(expr={'a': False}))
def test_plain_string(self):
dcp = DictComPy(model=MODELS['str'][0])
self.assertFalse(dcp.match(expr={'b': u'a'}))
self.assertFalse(dcp.match(expr={'a': 23}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertTrue(dcp.match(expr={'a': 'a'}))
self.assertTrue(dcp.match(expr={'a': u'a'}))
self.assertTrue(dcp.match(expr={'a': u''}))
self.assertTrue(dcp.match(expr={'a': ''}))
def test_plain_list(self):
dcp = DictComPy(model=MODELS['list'][0])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': []}))
self.assertTrue(dcp.match(expr={'a': [1]}))
self.assertTrue(dcp.match(expr={'a': [1, '1021', True]}))
dcp = DictComPy(model=MODELS['list'][1])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': []}))
dcp = DictComPy(model=MODELS['list'][2])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': []}))
dcp = DictComPy(model=MODELS['list'][3])
self.assertFalse(dcp.match(expr={'b': [1]}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True]}))
self.assertTrue(dcp.match(expr={'a': [1]}))
self.assertTrue(dcp.match(expr={'a': [1, 2, 3]}))
dcp = DictComPy(model=MODELS['list'][4])
self.assertFalse(dcp.match(expr={'b': []}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': [1]}))
self.assertFalse(dcp.match(expr={'a': [1, '1021', True, 1.0]}))
self.assertTrue(dcp.match(expr={'a': [1, '1021', True]}))
def test_plain_tuple(self):
dcp = DictComPy(model=MODELS['tuple'][0])
self.assertFalse(dcp.match(expr={'b': ()}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)})) # 1, <-- common mistake
self.assertTrue(dcp.match(expr={'a': (1, '1021', True)}))
dcp = DictComPy(model=MODELS['tuple'][1]) # ',' <--
self.assertFalse(dcp.match(expr={'b': (1,)}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': ()}))
self.assertFalse(dcp.match(expr={'a': (1, '1021', True)}))
self.assertFalse(dcp.match(expr={'a': ('',)}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
self.assertTrue(dcp.match(expr={'a': (1, 2, 3)}))
dcp = DictComPy(model=MODELS['tuple'][2]) # ',' <--
self.assertFalse(dcp.match(expr={'b': (1,)}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': ()}))
self.assertFalse(dcp.match(expr={'a': (1,)}))
self.assertFalse(dcp.match(expr={'a': (1, 2, 3)}))
self.assertFalse(dcp.match(expr={'a': (1, '1021', True, 1.0)}))
self.assertTrue(dcp.match(expr={'a': (1, '1021', True)}))
def test_nested_int(self):
dcp = DictComPy({'a': {'b': int}})
self.assertFalse(dcp.match(expr={'b': {'b': 1}}))
self.assertFalse(dcp.match(expr={'a': {'a': 1}}))
self.assertFalse(dcp.match(expr={'a': {'b': ''}}))
self.assertTrue(dcp.match(expr={'a': {'b': 1}}))
def test_In(self):
dcp = DictComPy({'a': (In, range(0,5,2))})
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 10}))
self.assertTrue(dcp.match(expr={'a': 2}))
def test_Like(self):
dcp = DictComPy({'a': (Like, '\d,\w+')})
self.assertFalse(dcp.match(expr={'a': '1,'}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': '10'}))
self.assertTrue(dcp.match(expr={'a': '1,0102dsada_dede'}))
def test_Date(self):
dcp = DictComPy({'a': (Date, '%Y-%d-%m')})
self.assertFalse(dcp.match(expr={'a': '2015-02-31'}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': '2015-32-01'}))
self.assertTrue(dcp.match(expr={'a': '2015-30-01'}))
def test_Excl(self):
dcp = DictComPy({'a': (Excl, ('1', '2'), {'1': int, '2': str})})
self.assertFalse(dcp.match(expr={'a': {'1': 's'}}))
self.assertFalse(dcp.match(expr={'a': {'2': 1}}))
self.assertFalse(dcp.match(expr={'a': {'1': 1, '2': 's'}}))
self.assertTrue(dcp.match(expr={'a': {'1': 1}}))
self.assertTrue(dcp.match(expr={'a': {'2': 's'}}))
def test_Opt(self):
dcp = DictComPy({'a': (Opt, int)})
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': 's'}))
self.assertFalse(dcp.match(expr={'a': True}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertTrue(dcp.match(expr={'a': 1}))
self.assertTrue(dcp.match(expr={'b': 1}))
def test_Eq(self):
dcp = DictComPy({'a': (Eq, 3)})
self.assertFalse(dcp.match(expr={'a': 1}))
self.assertFalse(dcp.match(expr={'a': 4}))
self.assertTrue(dcp.match(expr={'a': 3}))
dcp = DictComPy({'a': (Eq, dict)})
self.assertFalse(dcp.match(expr={'a': {}}))
self.assertFalse(dcp.match(expr={'a': list}))
self.assertTrue(dcp.match(expr={'a': dict}))
def test_Or_None(self):
dcp = DictComPy({'a': (Or_None, int)})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertTrue(dcp.match(expr={'a': None}))
self.assertTrue(dcp.match(expr={'a': 1}))
dcp = DictComPy({'a': (Or_None, (tuple, int))})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
def test_Or_Empty(self):
dcp = DictComPy({'a': (Or_Empty, {'b': int})})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': {}}))
self.assertTrue(dcp.match(expr={'a': {'b': 1}}))
dcp = DictComPy({'a': (Or_Empty, [int])})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ['df']}))
self.assertTrue(dcp.match(expr={'a': []}))
self.assertTrue(dcp.match(expr={'a': [1]}))
""" Failing
dcp = DictComPy({'a': (Or_Empty, (tuple, int))})
self.assertFalse(dcp.match(expr={'b': 1}))
self.assertFalse(dcp.match(expr={'a': 1.0}))
self.assertFalse(dcp.match(expr={'a': ''}))
self.assertFalse(dcp.match(expr={'a': False}))
self.assertFalse(dcp.match(expr={'a': []}))
self.assertFalse(dcp.match(expr={'a': None}))
self.assertFalse(dcp.match(expr={'a': ('df',)}))
self.assertTrue(dcp.match(expr={'a': ()}))
self.assertTrue(dcp.match(expr={'a': (1,)}))
"""
if __name__ == '__main__':
unittest.main() | en | 0.153813 | # TODO # model: (int, 1) -> funciona com toca. Les tuples son especials x) # faltaria afegir un parseig del model # 1, <-- common mistake # ',' <-- # ',' <-- Failing dcp = DictComPy({'a': (Or_Empty, (tuple, int))}) self.assertFalse(dcp.match(expr={'b': 1})) self.assertFalse(dcp.match(expr={'a': 1.0})) self.assertFalse(dcp.match(expr={'a': ''})) self.assertFalse(dcp.match(expr={'a': False})) self.assertFalse(dcp.match(expr={'a': []})) self.assertFalse(dcp.match(expr={'a': None})) self.assertFalse(dcp.match(expr={'a': ('df',)})) self.assertTrue(dcp.match(expr={'a': ()})) self.assertTrue(dcp.match(expr={'a': (1,)})) | 3.118237 | 3 |
Jupyter_Notebooks/Scripts/Correspondence_XML_parser.py | NEU-Libraries/dsg-mhs | 0 | 6620611 | <gh_stars>0
import re
import pandas as pd
import xml.etree.ElementTree as ET
# Read in file and get root of XML tree.
def get_root(xml_file):
tree = ET.parse(xml_file)
root = tree.getroot()
return root
# Get namespace of individual file from root element.
def get_namespace(root):
namespace = re.match(r"{(.*)}", str(root.tag))
ns = {"ns":namespace.group(1)}
return ns
def build_dataframe(list_of_files):
dataframe = []
for file in list_of_files:
try:
root = get_root(file)
ns = get_namespace(root)
reFile = str(re.search(r'.*/(.*.xml)', str(file)).group(1)) # get filename without path
date = root.find('.//ns:date/[@type="creation"]', ns).get('when') # get date.
source = root.find('.//ns:bibl//ns:author', ns).text # get source/author & target/recipient
target = root.find('.//ns:bibl//ns:recipient', ns).text
# Loops
# loop to get all references (persRef)
references_l = []
for ref in root.findall('.//ns:persRef', ns):
person = ref.get('ref')
references_l.append(person)
references = ','.join(references_l)
# loop to get subjects.
subject_l = []
for subject in root.findall('.//ns:subject', ns):
subject_l.append(subject.text)
subjects = ','.join(subject_l)
# loop to get all text within <div type="docbody">
text_l = []
for txt in root.findall('.//ns:div[@type="docbody"]', ns):
string = ''.join(ET.tostring(txt, encoding='unicode', method='text'))
clean_string = re.sub(r'[\t\n\s]+', ' ', string)
text_l.append(clean_string)
content = ' '.join(text_l)
row = {'file': reFile, 'date': date, 'source': source, 'target':target,
'subjects': subjects, 'references': references, 'text': content}
dataframe.append(row)
except:
print (file, '\n')
df = pd.DataFrame(dataframe)
return (df) | import re
import pandas as pd
import xml.etree.ElementTree as ET
# Read in file and get root of XML tree.
def get_root(xml_file):
tree = ET.parse(xml_file)
root = tree.getroot()
return root
# Get namespace of individual file from root element.
def get_namespace(root):
namespace = re.match(r"{(.*)}", str(root.tag))
ns = {"ns":namespace.group(1)}
return ns
def build_dataframe(list_of_files):
dataframe = []
for file in list_of_files:
try:
root = get_root(file)
ns = get_namespace(root)
reFile = str(re.search(r'.*/(.*.xml)', str(file)).group(1)) # get filename without path
date = root.find('.//ns:date/[@type="creation"]', ns).get('when') # get date.
source = root.find('.//ns:bibl//ns:author', ns).text # get source/author & target/recipient
target = root.find('.//ns:bibl//ns:recipient', ns).text
# Loops
# loop to get all references (persRef)
references_l = []
for ref in root.findall('.//ns:persRef', ns):
person = ref.get('ref')
references_l.append(person)
references = ','.join(references_l)
# loop to get subjects.
subject_l = []
for subject in root.findall('.//ns:subject', ns):
subject_l.append(subject.text)
subjects = ','.join(subject_l)
# loop to get all text within <div type="docbody">
text_l = []
for txt in root.findall('.//ns:div[@type="docbody"]', ns):
string = ''.join(ET.tostring(txt, encoding='unicode', method='text'))
clean_string = re.sub(r'[\t\n\s]+', ' ', string)
text_l.append(clean_string)
content = ' '.join(text_l)
row = {'file': reFile, 'date': date, 'source': source, 'target':target,
'subjects': subjects, 'references': references, 'text': content}
dataframe.append(row)
except:
print (file, '\n')
df = pd.DataFrame(dataframe)
return (df) | en | 0.793708 | # Read in file and get root of XML tree. # Get namespace of individual file from root element. # get filename without path # get date. # get source/author & target/recipient # Loops # loop to get all references (persRef) # loop to get subjects. # loop to get all text within <div type="docbody"> | 2.854278 | 3 |
c64/constants.py | thanasisk/binja-c64 | 0 | 6620612 | <filename>c64/constants.py
# coding=utf-8
"""
Copyright (c) 2021 <NAME>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
KERNAL = { 0xFF81: "SCINIT",
0xFF84: "IOINIT", #. Initialize CIA's, SID volume; setup memory configuration; set and start interrupt timer.
0xFF87: "RAMTAS",
0xFF8A: "RESTOR",
0xFF8D: "VECTOR",
0xFF90: "SETMSG",
0xFF93: "LSTNSA",
0xFF96: "TALKSA",
0xFF99: "MEMBOT",
0xFF9C: "MEMTOP",
0xFF9F: "SCNKEY",
0xFFA2: "SETTMO",
0xFFA5: "IECIN",
0xFFA8: "IECOUT",
0xFFAB: "UNTALK",
0xFFAE: "UNLSTN",
0xFFB1: "LISTEN",
0xFFB4: "TALK",
0xFFB7: "READST",
0xFFBA: "SETLFS",
0xFFBD: "SETNAM",
0xFFC0: "OPEN",
0xFFC3: "CLOSE",
0xFFC6: "CHKIN",
0xFFC9: "CHKOUT",
0xFFCC: "CLRCHN",
0xFFCF: "CHRIN",
0xFFD2: "CHROUT",
0xFFD5: "LOAD",
0xFFD8: "SAVE",
0xFFDB: "SETTIM",
0xFFDE: "RDTIM",
0xFFE1: "STOP",
0xFFE4: "GETIN",
0xFFE7: "CLALL",
0xFFEA: "UDTIM",
0xFFED: "SCREEN",
0xFFF0: "PLOT",
0xFFF3: "IOBASE" }
| <filename>c64/constants.py
# coding=utf-8
"""
Copyright (c) 2021 <NAME>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
KERNAL = { 0xFF81: "SCINIT",
0xFF84: "IOINIT", #. Initialize CIA's, SID volume; setup memory configuration; set and start interrupt timer.
0xFF87: "RAMTAS",
0xFF8A: "RESTOR",
0xFF8D: "VECTOR",
0xFF90: "SETMSG",
0xFF93: "LSTNSA",
0xFF96: "TALKSA",
0xFF99: "MEMBOT",
0xFF9C: "MEMTOP",
0xFF9F: "SCNKEY",
0xFFA2: "SETTMO",
0xFFA5: "IECIN",
0xFFA8: "IECOUT",
0xFFAB: "UNTALK",
0xFFAE: "UNLSTN",
0xFFB1: "LISTEN",
0xFFB4: "TALK",
0xFFB7: "READST",
0xFFBA: "SETLFS",
0xFFBD: "SETNAM",
0xFFC0: "OPEN",
0xFFC3: "CLOSE",
0xFFC6: "CHKIN",
0xFFC9: "CHKOUT",
0xFFCC: "CLRCHN",
0xFFCF: "CHRIN",
0xFFD2: "CHROUT",
0xFFD5: "LOAD",
0xFFD8: "SAVE",
0xFFDB: "SETTIM",
0xFFDE: "RDTIM",
0xFFE1: "STOP",
0xFFE4: "GETIN",
0xFFE7: "CLALL",
0xFFEA: "UDTIM",
0xFFED: "SCREEN",
0xFFF0: "PLOT",
0xFFF3: "IOBASE" }
| en | 0.760916 | # coding=utf-8 Copyright (c) 2021 <NAME> Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. #. Initialize CIA's, SID volume; setup memory configuration; set and start interrupt timer. | 1.600085 | 2 |
coursera/semana7/exerc_02.py | pedrobenevides2/Ciencia-de-Dados | 0 | 6620613 | <reponame>pedrobenevides2/Ciencia-de-Dados<gh_stars>0
x =int(input('digite a largura: '))
y= int(input('digite a altura: '))
x1=x
y1=y
while y>=1:
while x>0:
if x==1:
print("#",end="")
elif x==x1:
print("#", end='')
elif y==1:
print("#", end='')
elif y==y1:
print("#", end='')
else:
print(" ",end='')
x=x-1
print()
y=y-1
x=x1
| x =int(input('digite a largura: '))
y= int(input('digite a altura: '))
x1=x
y1=y
while y>=1:
while x>0:
if x==1:
print("#",end="")
elif x==x1:
print("#", end='')
elif y==1:
print("#", end='')
elif y==y1:
print("#", end='')
else:
print(" ",end='')
x=x-1
print()
y=y-1
x=x1 | none | 1 | 4.003368 | 4 | |
.makeversion.py | mangal-wg/pymangal | 3 | 6620614 | <reponame>mangal-wg/pymangal
import pymangal
import os
with open('.version', 'w') as f:
f.write(pymangal.__version__)
f.write("\n")
with open('.tag', 'r') as f:
t = f.readline().rstrip()
if not t == pymangal.__version__ :
os.system("git tag {0}".format(pymangal.__version__))
| import pymangal
import os
with open('.version', 'w') as f:
f.write(pymangal.__version__)
f.write("\n")
with open('.tag', 'r') as f:
t = f.readline().rstrip()
if not t == pymangal.__version__ :
os.system("git tag {0}".format(pymangal.__version__)) | none | 1 | 2.363528 | 2 | |
3Deep_Q_Network/agent.py | Mirocle007/Reinforcement_Learning | 1 | 6620615 | <filename>3Deep_Q_Network/agent.py
"""
Agent for the reinforcement learning, which learn from the environment and choose action.
"""
import numpy as np
import tensorflow as tf
def network(name, state, n_action, target_Q=None):
"""A simple 2 layer neural network
"""
n_state = state.shape[1].value
with tf.variable_scope(name):
# c_names(collections_names) are the collections to store variables
c_names, n_l1, w_initializer, b_initializer = (
["{}_params".format(name), tf.GraphKeys.GLOBAL_VARIABLES], 10,
tf.random_normal_initializer(0., 0.3),
tf.constant_initializer(0.1) # config of layers
)
# first layer.collections is used later when assign to target net
with tf.variable_scope("l1"):
w1 = tf.get_variable("w1",
[n_state, n_l1],
initializer=w_initializer,
collections=c_names)
b1 = tf.get_variable("b1",
[1, n_l1],
initializer=b_initializer,
collections=c_names)
l1 = tf.nn.relu(tf.matmul(state, w1) + b1)
# second layer. collections is used later when assign to target net
with tf.variable_scope("l2"):
w2 = tf.get_variable("w2",
[n_l1, n_action],
initializer=w_initializer,
collections=c_names)
b2 = tf.get_variable("b2",
[1, n_action],
initializer=b_initializer,
collections=c_names)
predict_Q = tf.matmul(l1, w2) + b2
if target_Q is not None:
with tf.variable_scope("loss"):
loss = tf.losses.mean_squared_error(target_Q, predict_Q)
return predict_Q, loss
else:
return predict_Q
class Agent(object):
def __init__(self, opt):
self.n_state = opt.n_state
self.n_action = len(opt.action_space)
self.actions = list(range(self.n_action))
self.gamma = opt.gamma
self.lr = opt.learning_rate
self.batch_size = opt.batch_size
self.epsilon = opt.epsilon
self.loss_history = []
self.memory_size = opt.memory_size
self.memory = np.zeros((self.memory_size, 2 * self.n_state + 2))
self.replace_target_iter = opt.replace_target_iter
self.learn_step_counter = 0
self._build_network()
tnet_params = tf.get_collection("target_net_params")
pnet_params = tf.get_collection("predict_net_params")
self.replace_target_op = [tf.assign(t, p) for t, p in zip(tnet_params, pnet_params)]
self.sess = tf.Session()
self.sess.run(tf.global_variables_initializer())
self.saver = tf.train.Saver()
if opt.output_graph:
# $ tensorboard --logdir=logs
tf.summary.FileWriter("logs/", self.sess.graph)
def _build_network(self):
self.target_Q = tf.placeholder(tf.float32, shape=(None,self.n_action))
self.state = tf.placeholder(tf.float32, shape=(None, self.n_state))
self.predict_Q, self.loss = network("predict_net", self.state,
self.n_action, target_Q=self.target_Q)
with tf.variable_scope("train"):
self._train_op = tf.train.RMSPropOptimizer(self.lr).minimize(self.loss)
self.next_state = tf.placeholder(tf.float32, [None, self.n_state], name="next_state")
self.next_Q = network("target_net", self.next_state, self.n_action)
def choose_action(self, state):
if np.random.randn() < self.epsilon:
state = state[np.newaxis, :]
actions = self.sess.run(
self.predict_Q,
feed_dict={self.state: state}
)
action = np.argmax(actions)
else:
action = np.random.choice(self.actions)
action = int(action)
return action
def store(self, state, action, reward, next_action):
if not hasattr(self, "memory_counter"):
self.memory_counter = 0
observation = np.hstack((state, action, reward, next_action))
index = self.memory_counter % self.memory_size
self.memory[index, :] = observation
self.memory_counter += 1
def learn(self):
# check to replace target net parameters
if self.learn_step_counter % self.replace_target_iter == 0:
self.sess.run(self.replace_target_op)
if self.learn_step_counter % self.replace_target_iter * 100 == 0:
self.save()
if self.memory_counter > self.memory_size:
sample_index = np.random.choice(self.memory_size, self.batch_size)
else:
sample_index = np.random.choice(self.memory_counter, self.batch_size)
batch_memory = self.memory[sample_index, :]
next_Q, predict_Q = self.sess.run(
[self.next_Q, self.predict_Q],
feed_dict={
self.next_state: batch_memory[:, -self.n_state: ],
self.state: batch_memory[:, :self.n_state]
}
)
target_Q = predict_Q.copy()
batch_index = np.arange(self.batch_size)
action_index = batch_memory[:, self.n_state].astype(int)
reward = batch_memory[:, self.n_state + 1]
target_Q[batch_index, action_index] = reward + self.gamma * np.max(next_Q, 1)
# train network
_, loss = self.sess.run(
[self._train_op, self.loss],
feed_dict={
self.state: batch_memory[:, :self.n_state],
self.target_Q: target_Q
}
)
self.loss_history.append(loss)
self.learn_step_counter += 1
def plot_cost(self):
import matplotlib.pyplot as plt
plt.plot(np.arange(len(self.loss_history)), self.loss_history)
plt.ylabel("loss")
plt.xlabel('training steps')
plt.show()
def save(self):
model_name = "./models/model_{}iter.ckpt".format(self.learn_step_counter)
save_path = self.saver.save(self.sess, model_name)
print("Model saved in path: {}".format(save_path))
def closs_session(self):
self.sess.close()
| <filename>3Deep_Q_Network/agent.py
"""
Agent for the reinforcement learning, which learn from the environment and choose action.
"""
import numpy as np
import tensorflow as tf
def network(name, state, n_action, target_Q=None):
"""A simple 2 layer neural network
"""
n_state = state.shape[1].value
with tf.variable_scope(name):
# c_names(collections_names) are the collections to store variables
c_names, n_l1, w_initializer, b_initializer = (
["{}_params".format(name), tf.GraphKeys.GLOBAL_VARIABLES], 10,
tf.random_normal_initializer(0., 0.3),
tf.constant_initializer(0.1) # config of layers
)
# first layer.collections is used later when assign to target net
with tf.variable_scope("l1"):
w1 = tf.get_variable("w1",
[n_state, n_l1],
initializer=w_initializer,
collections=c_names)
b1 = tf.get_variable("b1",
[1, n_l1],
initializer=b_initializer,
collections=c_names)
l1 = tf.nn.relu(tf.matmul(state, w1) + b1)
# second layer. collections is used later when assign to target net
with tf.variable_scope("l2"):
w2 = tf.get_variable("w2",
[n_l1, n_action],
initializer=w_initializer,
collections=c_names)
b2 = tf.get_variable("b2",
[1, n_action],
initializer=b_initializer,
collections=c_names)
predict_Q = tf.matmul(l1, w2) + b2
if target_Q is not None:
with tf.variable_scope("loss"):
loss = tf.losses.mean_squared_error(target_Q, predict_Q)
return predict_Q, loss
else:
return predict_Q
class Agent(object):
def __init__(self, opt):
self.n_state = opt.n_state
self.n_action = len(opt.action_space)
self.actions = list(range(self.n_action))
self.gamma = opt.gamma
self.lr = opt.learning_rate
self.batch_size = opt.batch_size
self.epsilon = opt.epsilon
self.loss_history = []
self.memory_size = opt.memory_size
self.memory = np.zeros((self.memory_size, 2 * self.n_state + 2))
self.replace_target_iter = opt.replace_target_iter
self.learn_step_counter = 0
self._build_network()
tnet_params = tf.get_collection("target_net_params")
pnet_params = tf.get_collection("predict_net_params")
self.replace_target_op = [tf.assign(t, p) for t, p in zip(tnet_params, pnet_params)]
self.sess = tf.Session()
self.sess.run(tf.global_variables_initializer())
self.saver = tf.train.Saver()
if opt.output_graph:
# $ tensorboard --logdir=logs
tf.summary.FileWriter("logs/", self.sess.graph)
def _build_network(self):
self.target_Q = tf.placeholder(tf.float32, shape=(None,self.n_action))
self.state = tf.placeholder(tf.float32, shape=(None, self.n_state))
self.predict_Q, self.loss = network("predict_net", self.state,
self.n_action, target_Q=self.target_Q)
with tf.variable_scope("train"):
self._train_op = tf.train.RMSPropOptimizer(self.lr).minimize(self.loss)
self.next_state = tf.placeholder(tf.float32, [None, self.n_state], name="next_state")
self.next_Q = network("target_net", self.next_state, self.n_action)
def choose_action(self, state):
if np.random.randn() < self.epsilon:
state = state[np.newaxis, :]
actions = self.sess.run(
self.predict_Q,
feed_dict={self.state: state}
)
action = np.argmax(actions)
else:
action = np.random.choice(self.actions)
action = int(action)
return action
def store(self, state, action, reward, next_action):
if not hasattr(self, "memory_counter"):
self.memory_counter = 0
observation = np.hstack((state, action, reward, next_action))
index = self.memory_counter % self.memory_size
self.memory[index, :] = observation
self.memory_counter += 1
def learn(self):
# check to replace target net parameters
if self.learn_step_counter % self.replace_target_iter == 0:
self.sess.run(self.replace_target_op)
if self.learn_step_counter % self.replace_target_iter * 100 == 0:
self.save()
if self.memory_counter > self.memory_size:
sample_index = np.random.choice(self.memory_size, self.batch_size)
else:
sample_index = np.random.choice(self.memory_counter, self.batch_size)
batch_memory = self.memory[sample_index, :]
next_Q, predict_Q = self.sess.run(
[self.next_Q, self.predict_Q],
feed_dict={
self.next_state: batch_memory[:, -self.n_state: ],
self.state: batch_memory[:, :self.n_state]
}
)
target_Q = predict_Q.copy()
batch_index = np.arange(self.batch_size)
action_index = batch_memory[:, self.n_state].astype(int)
reward = batch_memory[:, self.n_state + 1]
target_Q[batch_index, action_index] = reward + self.gamma * np.max(next_Q, 1)
# train network
_, loss = self.sess.run(
[self._train_op, self.loss],
feed_dict={
self.state: batch_memory[:, :self.n_state],
self.target_Q: target_Q
}
)
self.loss_history.append(loss)
self.learn_step_counter += 1
def plot_cost(self):
import matplotlib.pyplot as plt
plt.plot(np.arange(len(self.loss_history)), self.loss_history)
plt.ylabel("loss")
plt.xlabel('training steps')
plt.show()
def save(self):
model_name = "./models/model_{}iter.ckpt".format(self.learn_step_counter)
save_path = self.saver.save(self.sess, model_name)
print("Model saved in path: {}".format(save_path))
def closs_session(self):
self.sess.close()
| en | 0.791454 | Agent for the reinforcement learning, which learn from the environment and choose action. A simple 2 layer neural network # c_names(collections_names) are the collections to store variables # config of layers # first layer.collections is used later when assign to target net # second layer. collections is used later when assign to target net # $ tensorboard --logdir=logs # check to replace target net parameters # train network | 3.321245 | 3 |
online_pharmacy/online_pharmacy/urls.py | geekyJock8/online_pharmacy | 5 | 6620616 | from django.conf.urls import url,include
from django.contrib import admin
urlpatterns = [
url(r'^',include('Register_and_login.urls')),
url(r'^homepage/',include('MainPage.urls')),
url(r'^username/cart/',include('cart.urls')),
url(r'^username/',include('customer.urls')),
url(r'^pharmacy_name/',include('pharmacy.urls')),
url(r'^pharmacy_name/inventory',include('inventory.urls')),
url(r'^search/all_search=pcm',include('items.urls')),
url(r'^', include('order.urls')),
url(r'^admin/', admin.site.urls)
]
| from django.conf.urls import url,include
from django.contrib import admin
urlpatterns = [
url(r'^',include('Register_and_login.urls')),
url(r'^homepage/',include('MainPage.urls')),
url(r'^username/cart/',include('cart.urls')),
url(r'^username/',include('customer.urls')),
url(r'^pharmacy_name/',include('pharmacy.urls')),
url(r'^pharmacy_name/inventory',include('inventory.urls')),
url(r'^search/all_search=pcm',include('items.urls')),
url(r'^', include('order.urls')),
url(r'^admin/', admin.site.urls)
]
| none | 1 | 1.753483 | 2 | |
TestBot/test_cogs/poketcgFunctions/database.py | austinmh12/DiscordBots | 0 | 6620617 | from .. import sql, log
def initialise_db():
sql('poketcg', '''create table players (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
)'''
)
sql('poketcg', '''create table packs (
discord_id integer
,set_id text
,amount integer
)'''
)
sql('poketcg', '''create table cards (
discord_id integer
,card_id text
,amount integer
)'''
)
sql('poketcg', '''create table version (
version text
)'''
)
sql('poketcg', 'insert into version values (?)', ('1.0.0',))
def get_version():
df = sql('poketcg', 'select * from version')
if df.empty:
return ''
return df.to_dict('records')[0]['version']
def update_version(version):
sql('poketcg', 'delete from version')
sql('poketcg', 'insert into version values (?)', (version,))
def migrate_db(version):
current = get_version()
log.debug(current)
log.debug(version)
if version <= current:
return
log.debug('Migrating database')
migration_versions = [k for k in migration_steps if k > current]
migration_versions.sort()
for migration_version in migration_versions:
for step in migration_steps[migration_version]:
sql('poketcg', step)
update_version(version)
migration_steps = {
'1.1.0': [
"alter table players add column collections text default '{}'",
"alter table players add column collections_bought integer default 0",
"alter table players add column trainers text default '{}'",
"alter table players add column trainers_bought integer default 0",
"alter table players add column boosters text default '{}'",
"alter table players add column boosters_bought integer default 0"
],
'1.2.0': [
"alter table players add column daily_packs integer default 50",
"alter table players add column quiz_questions integer default 5",
"alter table players add column current_multiplier integer default 1",
"alter table players add column quiz_correct integer default 0"
],
'1.2.2': [
"""create table tmp_player (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
,daily_packs integer
,quiz_questions integer
,current_multiplier integer
,quiz_correct integer
) """,
"""insert into tmp_player select
discord_id
,cash
,daily_reset
,packs
,packs_opened
,packs_bought
,total_cash
,total_cards
,cards_sold
,daily_packs
,quiz_questions
,current_multiplier
,quiz_correct
from
players
""",
'drop table players',
"""create table players (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
,daily_packs integer
,quiz_questions integer
,current_multiplier integer
,quiz_correct integer
) """,
'insert into players select * from tmp_player',
'drop table tmp_player'
],
'1.2.3': [
'alter table players add column quiz_reset integer default 1629401801.1'
],
'1.3.0': [
"alter table players add column savelist text default '[]'"
],
'1.4.0': [
"alter table players add column permanent_mult integer default 0"
]
} | from .. import sql, log
def initialise_db():
sql('poketcg', '''create table players (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
)'''
)
sql('poketcg', '''create table packs (
discord_id integer
,set_id text
,amount integer
)'''
)
sql('poketcg', '''create table cards (
discord_id integer
,card_id text
,amount integer
)'''
)
sql('poketcg', '''create table version (
version text
)'''
)
sql('poketcg', 'insert into version values (?)', ('1.0.0',))
def get_version():
df = sql('poketcg', 'select * from version')
if df.empty:
return ''
return df.to_dict('records')[0]['version']
def update_version(version):
sql('poketcg', 'delete from version')
sql('poketcg', 'insert into version values (?)', (version,))
def migrate_db(version):
current = get_version()
log.debug(current)
log.debug(version)
if version <= current:
return
log.debug('Migrating database')
migration_versions = [k for k in migration_steps if k > current]
migration_versions.sort()
for migration_version in migration_versions:
for step in migration_steps[migration_version]:
sql('poketcg', step)
update_version(version)
migration_steps = {
'1.1.0': [
"alter table players add column collections text default '{}'",
"alter table players add column collections_bought integer default 0",
"alter table players add column trainers text default '{}'",
"alter table players add column trainers_bought integer default 0",
"alter table players add column boosters text default '{}'",
"alter table players add column boosters_bought integer default 0"
],
'1.2.0': [
"alter table players add column daily_packs integer default 50",
"alter table players add column quiz_questions integer default 5",
"alter table players add column current_multiplier integer default 1",
"alter table players add column quiz_correct integer default 0"
],
'1.2.2': [
"""create table tmp_player (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
,daily_packs integer
,quiz_questions integer
,current_multiplier integer
,quiz_correct integer
) """,
"""insert into tmp_player select
discord_id
,cash
,daily_reset
,packs
,packs_opened
,packs_bought
,total_cash
,total_cards
,cards_sold
,daily_packs
,quiz_questions
,current_multiplier
,quiz_correct
from
players
""",
'drop table players',
"""create table players (
discord_id integer
,cash integer
,daily_reset integer
,packs text
,packs_opened integer
,packs_bought integer
,total_cash integer
,total_cards integer
,cards_sold integer
,daily_packs integer
,quiz_questions integer
,current_multiplier integer
,quiz_correct integer
) """,
'insert into players select * from tmp_player',
'drop table tmp_player'
],
'1.2.3': [
'alter table players add column quiz_reset integer default 1629401801.1'
],
'1.3.0': [
"alter table players add column savelist text default '[]'"
],
'1.4.0': [
"alter table players add column permanent_mult integer default 0"
]
} | en | 0.433302 | create table players ( discord_id integer ,cash integer ,daily_reset integer ,packs text ,packs_opened integer ,packs_bought integer ,total_cash integer ,total_cards integer ,cards_sold integer ) create table packs ( discord_id integer ,set_id text ,amount integer ) create table cards ( discord_id integer ,card_id text ,amount integer ) create table version ( version text ) create table tmp_player ( discord_id integer ,cash integer ,daily_reset integer ,packs text ,packs_opened integer ,packs_bought integer ,total_cash integer ,total_cards integer ,cards_sold integer ,daily_packs integer ,quiz_questions integer ,current_multiplier integer ,quiz_correct integer ) insert into tmp_player select discord_id ,cash ,daily_reset ,packs ,packs_opened ,packs_bought ,total_cash ,total_cards ,cards_sold ,daily_packs ,quiz_questions ,current_multiplier ,quiz_correct from players create table players ( discord_id integer ,cash integer ,daily_reset integer ,packs text ,packs_opened integer ,packs_bought integer ,total_cash integer ,total_cards integer ,cards_sold integer ,daily_packs integer ,quiz_questions integer ,current_multiplier integer ,quiz_correct integer ) | 2.619636 | 3 |
rconweb/api/urls.py | ProfessorZ/hll_rcon_tool | 0 | 6620618 | <filename>rconweb/api/urls.py
from django.urls import path
from . import views
from . import auth
urlpatterns = [
path(name, func, name='name')
for name, func in views.commands
] + [
path('login', auth.do_login),
path('logout', auth.do_logout),
path('is_logged_in', auth.is_logged_in),
path('get_online_mods', auth.get_online_mods),
path('get_ingame_mods', auth.get_ingame_mods)
]
| <filename>rconweb/api/urls.py
from django.urls import path
from . import views
from . import auth
urlpatterns = [
path(name, func, name='name')
for name, func in views.commands
] + [
path('login', auth.do_login),
path('logout', auth.do_logout),
path('is_logged_in', auth.is_logged_in),
path('get_online_mods', auth.get_online_mods),
path('get_ingame_mods', auth.get_ingame_mods)
]
| none | 1 | 2.077484 | 2 | |
src/solana/_layouts/stake_instructions.py | yankev/solana-py | 0 | 6620619 | from enum import IntEnum
from construct import Switch # type: ignore
from construct import Int32ul, Int64ul, Int64sl, Pass # type: ignore
from construct import Struct as cStruct
from .shared import PUBLIC_KEY_LAYOUT
class StakeInstructionType(IntEnum):
"""Instruction types for staking program."""
INITIALIZE_STAKE_ACCOUNT = 0
DELEGATE_STAKE = 2
WITHDRAW_STAKE = 4
DEACTIVATE = 5
_AUTHORIZED_LAYOUT = cStruct(
"staker" / PUBLIC_KEY_LAYOUT,
"withdrawer" / PUBLIC_KEY_LAYOUT,
)
_LOCKUP_LAYOUT = cStruct(
"unix_timestamp" / Int64sl,
"epoch" / Int64ul,
"custodian" / PUBLIC_KEY_LAYOUT,
)
_INITIALIZE_STAKE_ACCOUNT_LAYOUT = cStruct(
"authorized" / _AUTHORIZED_LAYOUT,
"lockup" / _LOCKUP_LAYOUT,
)
_WITHDRAW_STAKE_ACCOUNT_LAYOUT = cStruct(
"lamports" / Int64ul,
)
STAKE_INSTRUCTIONS_LAYOUT = cStruct(
"instruction_type" / Int32ul,
"args"
/ Switch(
lambda this: this.instruction_type,
{
StakeInstructionType.INITIALIZE_STAKE_ACCOUNT: _INITIALIZE_STAKE_ACCOUNT_LAYOUT,
StakeInstructionType.DELEGATE_STAKE: Pass,
StakeInstructionType.DEACTIVATE: Pass,
StakeInstructionType.WITHDRAW_STAKE: _WITHDRAW_STAKE_ACCOUNT_LAYOUT,
},
),
)
| from enum import IntEnum
from construct import Switch # type: ignore
from construct import Int32ul, Int64ul, Int64sl, Pass # type: ignore
from construct import Struct as cStruct
from .shared import PUBLIC_KEY_LAYOUT
class StakeInstructionType(IntEnum):
"""Instruction types for staking program."""
INITIALIZE_STAKE_ACCOUNT = 0
DELEGATE_STAKE = 2
WITHDRAW_STAKE = 4
DEACTIVATE = 5
_AUTHORIZED_LAYOUT = cStruct(
"staker" / PUBLIC_KEY_LAYOUT,
"withdrawer" / PUBLIC_KEY_LAYOUT,
)
_LOCKUP_LAYOUT = cStruct(
"unix_timestamp" / Int64sl,
"epoch" / Int64ul,
"custodian" / PUBLIC_KEY_LAYOUT,
)
_INITIALIZE_STAKE_ACCOUNT_LAYOUT = cStruct(
"authorized" / _AUTHORIZED_LAYOUT,
"lockup" / _LOCKUP_LAYOUT,
)
_WITHDRAW_STAKE_ACCOUNT_LAYOUT = cStruct(
"lamports" / Int64ul,
)
STAKE_INSTRUCTIONS_LAYOUT = cStruct(
"instruction_type" / Int32ul,
"args"
/ Switch(
lambda this: this.instruction_type,
{
StakeInstructionType.INITIALIZE_STAKE_ACCOUNT: _INITIALIZE_STAKE_ACCOUNT_LAYOUT,
StakeInstructionType.DELEGATE_STAKE: Pass,
StakeInstructionType.DEACTIVATE: Pass,
StakeInstructionType.WITHDRAW_STAKE: _WITHDRAW_STAKE_ACCOUNT_LAYOUT,
},
),
)
| en | 0.589977 | # type: ignore # type: ignore Instruction types for staking program. | 2.17897 | 2 |
alembic/versions/47124d1df386_remove_password.py | morelab/labmanager | 2 | 6620620 | <reponame>morelab/labmanager
"""Remove password
Revision ID: <PASSWORD>
Revises: <KEY>
Create Date: 2016-11-03 17:12:14.046930
"""
# revision identifiers, used by Alembic.
revision = '4<PASSWORD>'
down_revision = '1545f<PASSWORD>1cd'
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import mysql
def upgrade():
### commands auto generated by Alembic - please adjust! ###
try:
op.drop_column('siway_user', u'password')
except:
pass
### end Alembic commands ###
pass
def downgrade():
### commands auto generated by Alembic - please adjust! ###
try:
op.add_column('siway_user', sa.Column(u'password', mysql.VARCHAR(length=255), nullable=False))
except:
pass
### end Alembic commands ###
| """Remove password
Revision ID: <PASSWORD>
Revises: <KEY>
Create Date: 2016-11-03 17:12:14.046930
"""
# revision identifiers, used by Alembic.
revision = '4<PASSWORD>'
down_revision = '1545f<PASSWORD>1cd'
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import mysql
def upgrade():
### commands auto generated by Alembic - please adjust! ###
try:
op.drop_column('siway_user', u'password')
except:
pass
### end Alembic commands ###
pass
def downgrade():
### commands auto generated by Alembic - please adjust! ###
try:
op.add_column('siway_user', sa.Column(u'password', mysql.VARCHAR(length=255), nullable=False))
except:
pass
### end Alembic commands ### | en | 0.525419 | Remove password Revision ID: <PASSWORD> Revises: <KEY> Create Date: 2016-11-03 17:12:14.046930 # revision identifiers, used by Alembic. ### commands auto generated by Alembic - please adjust! ### ### end Alembic commands ### ### commands auto generated by Alembic - please adjust! ### ### end Alembic commands ### | 1.256903 | 1 |
eveil/map.py | pjfichet/eveil | 0 | 6620621 | <filename>eveil/map.py
# Copyright (C) 2018 <NAME>
# <pierrejean dot fichet at posteo dot net>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
# This submodule implements a directed graph.
# The path algorithm comes from: https://www.python.org/doc/essays/graphs/
# Some other ideas come from:
# https://triangleinequality.wordpress.com/2013/08/21/graphs-as-objects-in-python/
from .template import Template
from .item import Container
from .message import pose, expose_format, info
from datetime import datetime, timedelta
class Map():
"""The Map class implements a graph: rooms are nodes, and links
are edges. Rooms and links instances should be created from a Map
object, using the new_room and new_link methods."""
def __init__(self, game):
self.game = game
self.rooms = []
self.links = []
self.linklists = []
def new_room(self, region, uid):
room = Room(self.game, region, uid)
self.rooms.append(room)
return room
def new_link(self, source, target):
# First, our link is a simple list
link = [source, target]
if link in self.linklists:
self.game.log("There is yet a link from room {} to room {}."
.format(source.shortdesc, target.shortdesc)
)
return
self.linklists.append(link)
# Now, we create a true Link instance
link = Link(source, target)
self.links.append(link)
source.add_link(link)
return link
def path(self, source, target, path=[]):
""" Returns the shortest path from source to target.
Comes from: https://www.python.org/doc/essays/graphs/
"""
path = path + [source]
if source == target:
return path
if source not in self.rooms:
return None
shortest = None
for room in source.get_targets():
if room not in path:
newpath = self.path(room, target, path)
if newpath:
if not shortest or len(newpath) < len(shortest):
shortest = newpath
return shortest
class Link():
""" An unidirectional link between two rooms."""
def __init__(self, source, target):
self.rooms = [source, target]
self.source = source
self.target = target
# pose_leave and pose_enter define the characters'
# automated poses when they leave a room and
# enter another.
# self.pose_move = None
# self.pose_leave = None
# self.pose_enter = None
self.door = None
def move(self, character):
self.leave(character)
character.queue.add(self.enter, character)
def leave(self, character):
pose(character, "/Il se dirige vers {}."
.format(self.target.shortdesc))
def enter(self, character):
pose(character, "/Il quitte les environs en rejoignant {}."
.format(self.target.shortdesc))
self.source.del_character(character)
self.target.send_longdesc(character)
self.target.add_character(character)
character.set_room(self.target)
pose(character, "/Il arrive par ici depuis {}."
.format(self.source.shortdesc))
class Door():
"""A door."""
def __init__(self):
self.is_opened = True
self.can_close = False
self.is_closed = False
self.can_lock = False
self.is_locked = False
self.key = None
class Room():
NEVER = datetime(2000, 1, 1)
RPDELTA = timedelta(minutes=15)
def __init__(self, game, region, uid):
self.game = game
self.region = region
self.uid = region + '_' + uid
if self.game.db.has('room', self.uid):
self.data = self.game.db.get('room', self.uid)
self.container = Container(self.game, self.data['container'])
else:
self.data = {
'container': self.game.db.uid()
}
self.container = Container(self.game, self.data['container'])
self.container.set_volume(10000)
self.game.db.put('room', self.uid, self.data)
self.shortdesc = None
self.longdesc = None
self.links = []
self.sources = []
self.targets = []
self.characters = []
self.next_rp = Room.NEVER
def short(self, text):
"""Sets the short description (title)."""
self.shortdesc = text
def long(self, text, dictionary={}):
"""Sets the long description."""
self.longdesc = Template(
"<h3>{{room.shortdesc}}</h3>"
+ text
#+ "<p>{{list_char}}</p>",
+ "<p>{{list_item}}</p><p>{{list_char}}</p>",
dictionary)
def add_link(self, link):
if self in link.rooms and link not in self.links:
self.links.append(link)
if link.source == self:
self.targets.append(link)
else:
self.sources.append(link)
def get_sources(self):
""" Return the list of rooms from which one can come here."""
return [link.source for link in self.links]
def get_targets(self):
""" Return the list of rooms one can go from here."""
return [link.target for link in self.targets]
def get_target_link(self, target):
""" Return the link leading to the target room."""
for link in self.targets:
if link.target == target:
return link
def get_source_link(self, source):
""" Return the link by which one can come from source room."""
for link in self.sources:
if link.source == source:
return link
def add_character(self, character):
""" add a character to the room."""
self.characters.append(character)
# Give a chance to players to have RP, even if they're not
# exposing yet.
if len(self.characters) > 1:
self.next_rp = datetime.now() + Room.RPDELTA
def del_character(self, character):
"""Removes a character form the rom."""
self.characters.remove(character)
if len(self.characters) < 2:
# A character alone is not having RP.
self.next_rp = Room.NEVER
def send_longdesc(self, character):
""" Send the long description to a character."""
list_char = ", ".join(
[expose_format(char, character, char.data['pose'])
for char in self.characters])
if list_char:
list_char += "."
list_item = ""
if self.container.items:
list_item = ", ".join([item.data['roomdesc']
for item in self.container.items])
list_item = list_item.capitalize() + "."
character.player.client.send(self.longdesc.render({
"character": character,
"room": self,
"list_char": list_char,
"list_item": list_item,
}))
def move(self, character, word):
""" Move a character to an adjacent room. """
for link in self.targets:
if word in link.target.shortdesc:
link.move(character)
return
info(character.player, "Aller où?")
def rp(self):
""" Update the RP status of the room."""
if len(self.characters) > 1:
self.next_rp = datetime.now() + Room.RPDELTA
def has_rp(self, now):
""" Check if the room is RP active."""
# self.del_character() takes care a lonely character
# won't have RP.
return bool(self.next_rp >= now)
| <filename>eveil/map.py
# Copyright (C) 2018 <NAME>
# <pierrejean dot fichet at posteo dot net>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
# This submodule implements a directed graph.
# The path algorithm comes from: https://www.python.org/doc/essays/graphs/
# Some other ideas come from:
# https://triangleinequality.wordpress.com/2013/08/21/graphs-as-objects-in-python/
from .template import Template
from .item import Container
from .message import pose, expose_format, info
from datetime import datetime, timedelta
class Map():
"""The Map class implements a graph: rooms are nodes, and links
are edges. Rooms and links instances should be created from a Map
object, using the new_room and new_link methods."""
def __init__(self, game):
self.game = game
self.rooms = []
self.links = []
self.linklists = []
def new_room(self, region, uid):
room = Room(self.game, region, uid)
self.rooms.append(room)
return room
def new_link(self, source, target):
# First, our link is a simple list
link = [source, target]
if link in self.linklists:
self.game.log("There is yet a link from room {} to room {}."
.format(source.shortdesc, target.shortdesc)
)
return
self.linklists.append(link)
# Now, we create a true Link instance
link = Link(source, target)
self.links.append(link)
source.add_link(link)
return link
def path(self, source, target, path=[]):
""" Returns the shortest path from source to target.
Comes from: https://www.python.org/doc/essays/graphs/
"""
path = path + [source]
if source == target:
return path
if source not in self.rooms:
return None
shortest = None
for room in source.get_targets():
if room not in path:
newpath = self.path(room, target, path)
if newpath:
if not shortest or len(newpath) < len(shortest):
shortest = newpath
return shortest
class Link():
""" An unidirectional link between two rooms."""
def __init__(self, source, target):
self.rooms = [source, target]
self.source = source
self.target = target
# pose_leave and pose_enter define the characters'
# automated poses when they leave a room and
# enter another.
# self.pose_move = None
# self.pose_leave = None
# self.pose_enter = None
self.door = None
def move(self, character):
self.leave(character)
character.queue.add(self.enter, character)
def leave(self, character):
pose(character, "/Il se dirige vers {}."
.format(self.target.shortdesc))
def enter(self, character):
pose(character, "/Il quitte les environs en rejoignant {}."
.format(self.target.shortdesc))
self.source.del_character(character)
self.target.send_longdesc(character)
self.target.add_character(character)
character.set_room(self.target)
pose(character, "/Il arrive par ici depuis {}."
.format(self.source.shortdesc))
class Door():
"""A door."""
def __init__(self):
self.is_opened = True
self.can_close = False
self.is_closed = False
self.can_lock = False
self.is_locked = False
self.key = None
class Room():
NEVER = datetime(2000, 1, 1)
RPDELTA = timedelta(minutes=15)
def __init__(self, game, region, uid):
self.game = game
self.region = region
self.uid = region + '_' + uid
if self.game.db.has('room', self.uid):
self.data = self.game.db.get('room', self.uid)
self.container = Container(self.game, self.data['container'])
else:
self.data = {
'container': self.game.db.uid()
}
self.container = Container(self.game, self.data['container'])
self.container.set_volume(10000)
self.game.db.put('room', self.uid, self.data)
self.shortdesc = None
self.longdesc = None
self.links = []
self.sources = []
self.targets = []
self.characters = []
self.next_rp = Room.NEVER
def short(self, text):
"""Sets the short description (title)."""
self.shortdesc = text
def long(self, text, dictionary={}):
"""Sets the long description."""
self.longdesc = Template(
"<h3>{{room.shortdesc}}</h3>"
+ text
#+ "<p>{{list_char}}</p>",
+ "<p>{{list_item}}</p><p>{{list_char}}</p>",
dictionary)
def add_link(self, link):
if self in link.rooms and link not in self.links:
self.links.append(link)
if link.source == self:
self.targets.append(link)
else:
self.sources.append(link)
def get_sources(self):
""" Return the list of rooms from which one can come here."""
return [link.source for link in self.links]
def get_targets(self):
""" Return the list of rooms one can go from here."""
return [link.target for link in self.targets]
def get_target_link(self, target):
""" Return the link leading to the target room."""
for link in self.targets:
if link.target == target:
return link
def get_source_link(self, source):
""" Return the link by which one can come from source room."""
for link in self.sources:
if link.source == source:
return link
def add_character(self, character):
""" add a character to the room."""
self.characters.append(character)
# Give a chance to players to have RP, even if they're not
# exposing yet.
if len(self.characters) > 1:
self.next_rp = datetime.now() + Room.RPDELTA
def del_character(self, character):
"""Removes a character form the rom."""
self.characters.remove(character)
if len(self.characters) < 2:
# A character alone is not having RP.
self.next_rp = Room.NEVER
def send_longdesc(self, character):
""" Send the long description to a character."""
list_char = ", ".join(
[expose_format(char, character, char.data['pose'])
for char in self.characters])
if list_char:
list_char += "."
list_item = ""
if self.container.items:
list_item = ", ".join([item.data['roomdesc']
for item in self.container.items])
list_item = list_item.capitalize() + "."
character.player.client.send(self.longdesc.render({
"character": character,
"room": self,
"list_char": list_char,
"list_item": list_item,
}))
def move(self, character, word):
""" Move a character to an adjacent room. """
for link in self.targets:
if word in link.target.shortdesc:
link.move(character)
return
info(character.player, "Aller où?")
def rp(self):
""" Update the RP status of the room."""
if len(self.characters) > 1:
self.next_rp = datetime.now() + Room.RPDELTA
def has_rp(self, now):
""" Check if the room is RP active."""
# self.del_character() takes care a lonely character
# won't have RP.
return bool(self.next_rp >= now)
| en | 0.849813 | # Copyright (C) 2018 <NAME> # <pierrejean dot fichet at posteo dot net> # # Permission to use, copy, modify, and/or distribute this software for any # purpose with or without fee is hereby granted, provided that the above # copyright notice and this permission notice appear in all copies. # # THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES # WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF # MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR # ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES # WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN # ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF # OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. # This submodule implements a directed graph. # The path algorithm comes from: https://www.python.org/doc/essays/graphs/ # Some other ideas come from: # https://triangleinequality.wordpress.com/2013/08/21/graphs-as-objects-in-python/ The Map class implements a graph: rooms are nodes, and links are edges. Rooms and links instances should be created from a Map object, using the new_room and new_link methods. # First, our link is a simple list # Now, we create a true Link instance Returns the shortest path from source to target. Comes from: https://www.python.org/doc/essays/graphs/ An unidirectional link between two rooms. # pose_leave and pose_enter define the characters' # automated poses when they leave a room and # enter another. # self.pose_move = None # self.pose_leave = None # self.pose_enter = None A door. Sets the short description (title). Sets the long description. #+ "<p>{{list_char}}</p>", Return the list of rooms from which one can come here. Return the list of rooms one can go from here. Return the link leading to the target room. Return the link by which one can come from source room. add a character to the room. # Give a chance to players to have RP, even if they're not # exposing yet. Removes a character form the rom. # A character alone is not having RP. Send the long description to a character. Move a character to an adjacent room. Update the RP status of the room. Check if the room is RP active. # self.del_character() takes care a lonely character # won't have RP. | 2.49074 | 2 |
pimpd/fonts.py | eprst/pimpd | 1 | 6620622 | <reponame>eprst/pimpd<gh_stars>1-10
from PIL import ImageFont
import os.path
if os.path.exists('Arial.ttf'):
DEFAULT_FONT = 'Arial.ttf'
else:
DEFAULT_FONT = 'DejaVuSans.ttf'
DEFAULT_FONT_12 = ImageFont.truetype(DEFAULT_FONT, 12)
DEFAULT_FONT_14 = ImageFont.truetype(DEFAULT_FONT, 14)
#DEFAULT_FONT = 'NotoSans-Regular.ttf'
#DEFAULT_FONT_12 = ImageFont.truetype(DEFAULT_FONT, 11)
#DEFAULT_FONT_14 = ImageFont.truetype(DEFAULT_FONT, 13)
| from PIL import ImageFont
import os.path
if os.path.exists('Arial.ttf'):
DEFAULT_FONT = 'Arial.ttf'
else:
DEFAULT_FONT = 'DejaVuSans.ttf'
DEFAULT_FONT_12 = ImageFont.truetype(DEFAULT_FONT, 12)
DEFAULT_FONT_14 = ImageFont.truetype(DEFAULT_FONT, 14)
#DEFAULT_FONT = 'NotoSans-Regular.ttf'
#DEFAULT_FONT_12 = ImageFont.truetype(DEFAULT_FONT, 11)
#DEFAULT_FONT_14 = ImageFont.truetype(DEFAULT_FONT, 13) | en | 0.502798 | #DEFAULT_FONT = 'NotoSans-Regular.ttf' #DEFAULT_FONT_12 = ImageFont.truetype(DEFAULT_FONT, 11) #DEFAULT_FONT_14 = ImageFont.truetype(DEFAULT_FONT, 13) | 2.548538 | 3 |
api/picklists/helpers.py | django-doctor/lite-api | 3 | 6620623 | from api.core.exceptions import NotFoundError
from api.picklists.models import PicklistItem
def get_picklist_item(pk):
try:
return PicklistItem.objects.get(pk=pk)
except PicklistItem.DoesNotExist:
raise NotFoundError({"picklist_item": "Picklist item not found - " + str(pk)})
| from api.core.exceptions import NotFoundError
from api.picklists.models import PicklistItem
def get_picklist_item(pk):
try:
return PicklistItem.objects.get(pk=pk)
except PicklistItem.DoesNotExist:
raise NotFoundError({"picklist_item": "Picklist item not found - " + str(pk)})
| none | 1 | 2.599634 | 3 | |
mapps/migrations/0001_initial.py | fossabot/mendelmd | 33 | 6620624 | # Generated by Django 2.1.4 on 2018-12-27 08:50
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='App',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=255)),
('status', models.CharField(max_length=255)),
('category', models.CharField(max_length=255)),
('source', models.CharField(blank=True, max_length=600, null=True)),
('repository', models.CharField(blank=True, max_length=600, null=True)),
('install', models.CharField(blank=True, max_length=600, null=True)),
('main', models.CharField(blank=True, max_length=600, null=True)),
('type', models.CharField(max_length=255)),
('config', django.contrib.postgres.fields.jsonb.JSONField(blank=True, null=True)),
('user', models.ForeignKey(editable=False, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
]
| # Generated by Django 2.1.4 on 2018-12-27 08:50
from django.conf import settings
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='App',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('name', models.CharField(max_length=255)),
('status', models.CharField(max_length=255)),
('category', models.CharField(max_length=255)),
('source', models.CharField(blank=True, max_length=600, null=True)),
('repository', models.CharField(blank=True, max_length=600, null=True)),
('install', models.CharField(blank=True, max_length=600, null=True)),
('main', models.CharField(blank=True, max_length=600, null=True)),
('type', models.CharField(max_length=255)),
('config', django.contrib.postgres.fields.jsonb.JSONField(blank=True, null=True)),
('user', models.ForeignKey(editable=False, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
],
),
]
| en | 0.726127 | # Generated by Django 2.1.4 on 2018-12-27 08:50 | 1.821649 | 2 |
op_robot_tests/tests_files/brokers/openprocurement_client_helper.py | dobruy2517/robot_tests_kap | 0 | 6620625 | <filename>op_robot_tests/tests_files/brokers/openprocurement_client_helper.py
from openprocurement_client.client import Client
from openprocurement_client.utils import get_tender_id_by_uaid
def prepare_api_wrapper(key, host_url, api_version):
return Client(key, host_url, api_version)
| <filename>op_robot_tests/tests_files/brokers/openprocurement_client_helper.py
from openprocurement_client.client import Client
from openprocurement_client.utils import get_tender_id_by_uaid
def prepare_api_wrapper(key, host_url, api_version):
return Client(key, host_url, api_version)
| none | 1 | 1.827399 | 2 | |
Source/FaceRecognition/Agents/FakeDetectionAgent.py | robertkarol/ReDe-Multiagent-Face-Recognition-System | 0 | 6620626 | from Agents.SystemAgent import SystemAgent
from Domain.Connection import Connection
from Domain.RecognitionRequest import RecognitionRequest
from Domain.RecognitionResponse import RecognitionResponse
from Utils.DatasetHelpers import DatasetHelpers
from concurrent.futures.thread import ThreadPoolExecutor
from spade.behaviour import PeriodicBehaviour, CyclicBehaviour
import asyncio
import codecs
import io
import random
class FakeDetectionAgent(SystemAgent):
class FakeDetectionBehavior(PeriodicBehaviour):
def __init__(self, outer_ref, period):
super().__init__(period=period)
self.__outer_ref: FakeDetectionAgent = outer_ref
try:
self.__face_images = DatasetHelpers.load_images(self.__outer_ref.data_directory)
except FileNotFoundError as error:
self.__outer_ref.log(f"Error loading files: {error}", "critical")
self.__outer_ref.stop()
async def on_start(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} starting fake detection. . .", "info")
async def run(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} sending face image. . .", "info")
image = self.__get_random_face_image()
request = RecognitionRequest(str(self.__outer_ref.jid), self.__outer_ref.agent_location,
self.__image_to_base64(image), self.__outer_ref.generate_outcome,
base64encoded=True)
data = str.encode(RecognitionRequest.serialize(request))
try:
await self.__outer_ref._connection.write_data(data)
except ConnectionError as error:
self.__outer_ref.log(f"Error writing to connection: {error}", "critical")
self.kill()
self.__outer_ref.stop()
self.__outer_ref.log(f"{self.__outer_ref.jid} done sending face image . . .", "info")
async def on_end(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} ending fake detection. . .", "info")
def __image_to_base64(self, image):
byte = io.BytesIO()
image.save(byte, 'JPEG')
return codecs.encode(byte.getvalue(), 'base64').decode()
def __get_random_face_image(self):
return random.choice(self.__face_images)
class ResponseReceiverBehavior(CyclicBehaviour):
def __init__(self, outer_ref):
super().__init__()
self.__outer_ref: FakeDetectionAgent = outer_ref
async def on_start(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} starting responses receiver. . .", "info")
async def run(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} waiting for response. . .", "info")
try:
data = await self.__outer_ref._connection.read_data()
if not data:
self.kill()
self.__outer_ref.log(f"{self.__outer_ref.jid} received: "
f"{RecognitionResponse.deserialize(data)!r}", "info")
except ConnectionError as error:
self.__outer_ref.log(f"Error reading from connection: {error}", "critical")
self.kill()
self.__outer_ref.stop()
self.__outer_ref.log(f"{self.__outer_ref.jid} done processing response . . .", "info")
async def on_end(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} ending responses receiver. . .", "info")
def __init__(self, jid: str, password: str, agent_location: str, data_directory: str, executor: ThreadPoolExecutor,
recognition_system_ip: str, recognition_system_port: int, detection_interval: int = 1,
generate_outcome: bool = False, message_checking_interval: int = 5, verify_security: bool = False):
super().__init__(jid, password, executor, verify_security, message_checking_interval)
self.__agent_location = agent_location
self.__data_directory = data_directory
self.__recognition_system_ip = recognition_system_ip
self.__recognition_system_port = recognition_system_port
self.__detection_interval = detection_interval
self.__generate_outcome = generate_outcome
self._connection: Connection
@property
def agent_location(self):
return self.__agent_location
@property
def data_directory(self):
return self.__data_directory
@property
def detection_interval(self):
return self.__detection_interval
@property
def generate_outcome(self):
return self.__generate_outcome
@property
def recognition_system_ip(self):
return self.__recognition_system_ip
@property
def recognition_system_port(self):
return self.__recognition_system_port
async def setup(self):
await super().setup()
reader_stream, writer_stream = \
await asyncio.open_connection(self.__recognition_system_ip, self.__recognition_system_port)
self._connection = Connection(str(self.jid), reader_stream, writer_stream)
detection_behavior = self.FakeDetectionBehavior(self, self.detection_interval)
receiver_behavior = self.ResponseReceiverBehavior(self)
self.add_behaviour(detection_behavior)
self.add_behaviour(receiver_behavior)
def stop(self):
self._connection.close()
return super().stop()
| from Agents.SystemAgent import SystemAgent
from Domain.Connection import Connection
from Domain.RecognitionRequest import RecognitionRequest
from Domain.RecognitionResponse import RecognitionResponse
from Utils.DatasetHelpers import DatasetHelpers
from concurrent.futures.thread import ThreadPoolExecutor
from spade.behaviour import PeriodicBehaviour, CyclicBehaviour
import asyncio
import codecs
import io
import random
class FakeDetectionAgent(SystemAgent):
class FakeDetectionBehavior(PeriodicBehaviour):
def __init__(self, outer_ref, period):
super().__init__(period=period)
self.__outer_ref: FakeDetectionAgent = outer_ref
try:
self.__face_images = DatasetHelpers.load_images(self.__outer_ref.data_directory)
except FileNotFoundError as error:
self.__outer_ref.log(f"Error loading files: {error}", "critical")
self.__outer_ref.stop()
async def on_start(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} starting fake detection. . .", "info")
async def run(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} sending face image. . .", "info")
image = self.__get_random_face_image()
request = RecognitionRequest(str(self.__outer_ref.jid), self.__outer_ref.agent_location,
self.__image_to_base64(image), self.__outer_ref.generate_outcome,
base64encoded=True)
data = str.encode(RecognitionRequest.serialize(request))
try:
await self.__outer_ref._connection.write_data(data)
except ConnectionError as error:
self.__outer_ref.log(f"Error writing to connection: {error}", "critical")
self.kill()
self.__outer_ref.stop()
self.__outer_ref.log(f"{self.__outer_ref.jid} done sending face image . . .", "info")
async def on_end(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} ending fake detection. . .", "info")
def __image_to_base64(self, image):
byte = io.BytesIO()
image.save(byte, 'JPEG')
return codecs.encode(byte.getvalue(), 'base64').decode()
def __get_random_face_image(self):
return random.choice(self.__face_images)
class ResponseReceiverBehavior(CyclicBehaviour):
def __init__(self, outer_ref):
super().__init__()
self.__outer_ref: FakeDetectionAgent = outer_ref
async def on_start(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} starting responses receiver. . .", "info")
async def run(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} waiting for response. . .", "info")
try:
data = await self.__outer_ref._connection.read_data()
if not data:
self.kill()
self.__outer_ref.log(f"{self.__outer_ref.jid} received: "
f"{RecognitionResponse.deserialize(data)!r}", "info")
except ConnectionError as error:
self.__outer_ref.log(f"Error reading from connection: {error}", "critical")
self.kill()
self.__outer_ref.stop()
self.__outer_ref.log(f"{self.__outer_ref.jid} done processing response . . .", "info")
async def on_end(self):
self.__outer_ref.log(f"{self.__outer_ref.jid} ending responses receiver. . .", "info")
def __init__(self, jid: str, password: str, agent_location: str, data_directory: str, executor: ThreadPoolExecutor,
recognition_system_ip: str, recognition_system_port: int, detection_interval: int = 1,
generate_outcome: bool = False, message_checking_interval: int = 5, verify_security: bool = False):
super().__init__(jid, password, executor, verify_security, message_checking_interval)
self.__agent_location = agent_location
self.__data_directory = data_directory
self.__recognition_system_ip = recognition_system_ip
self.__recognition_system_port = recognition_system_port
self.__detection_interval = detection_interval
self.__generate_outcome = generate_outcome
self._connection: Connection
@property
def agent_location(self):
return self.__agent_location
@property
def data_directory(self):
return self.__data_directory
@property
def detection_interval(self):
return self.__detection_interval
@property
def generate_outcome(self):
return self.__generate_outcome
@property
def recognition_system_ip(self):
return self.__recognition_system_ip
@property
def recognition_system_port(self):
return self.__recognition_system_port
async def setup(self):
await super().setup()
reader_stream, writer_stream = \
await asyncio.open_connection(self.__recognition_system_ip, self.__recognition_system_port)
self._connection = Connection(str(self.jid), reader_stream, writer_stream)
detection_behavior = self.FakeDetectionBehavior(self, self.detection_interval)
receiver_behavior = self.ResponseReceiverBehavior(self)
self.add_behaviour(detection_behavior)
self.add_behaviour(receiver_behavior)
def stop(self):
self._connection.close()
return super().stop()
| none | 1 | 2.337339 | 2 | |
Day-1/code.py | vaithak/Advent-of-Code-2021 | 0 | 6620627 | <filename>Day-1/code.py
def F(win_size):
prev_arr = []
prev_sum = 0
win_start_idx = 0 # essentially prev_arr is a circular window.
increased_cnt = 0
with open('input.txt') as f:
for x in f:
x = int(x)
if len(prev_arr) == win_size:
diff_sum = (x - prev_arr[win_start_idx])
increased_cnt += diff_sum > 0
prev_sum += diff_sum
prev_arr[win_start_idx] = x
win_start_idx = (win_start_idx + 1)%win_size
else:
prev_arr.append(x)
prev_sum += x
print("\tlast number: ", x)
print("\tcount : ", increased_cnt)
print("Part 1:")
F(1)
print("Part 2:")
F(3)
| <filename>Day-1/code.py
def F(win_size):
prev_arr = []
prev_sum = 0
win_start_idx = 0 # essentially prev_arr is a circular window.
increased_cnt = 0
with open('input.txt') as f:
for x in f:
x = int(x)
if len(prev_arr) == win_size:
diff_sum = (x - prev_arr[win_start_idx])
increased_cnt += diff_sum > 0
prev_sum += diff_sum
prev_arr[win_start_idx] = x
win_start_idx = (win_start_idx + 1)%win_size
else:
prev_arr.append(x)
prev_sum += x
print("\tlast number: ", x)
print("\tcount : ", increased_cnt)
print("Part 1:")
F(1)
print("Part 2:")
F(3)
| en | 0.950773 | # essentially prev_arr is a circular window. | 3.398809 | 3 |
Joe #2 Monte-Carlo Control in Easy21/easy21.py | analog-rl/Easy21 | 6 | 6620628 | from enum import Enum
import copy
import random
random.seed(1)
class State:
def __init__(self, dealer_card, player_card, is_terminal=False):
"""
:type self.is_terminal: bool
:type self.dealer: int
:type self.player: int
"""
self.dealer = dealer_card.value
self.player = player_card.value
self.term = is_terminal
self.r = 0
class Card:
def __init__(self, force_black=False):
"""
:type self.value: int
"""
self.value = random.randint(1,10)
self.absolute_value = self.value
if force_black or random.randint(1,3) != 1:
self.is_black = True
else:
self.is_black = False
self.value = 0 - self.value
self.is_red = not self.is_black
class Actions(Enum):
# Possible actions
hit = 0
stick = 1
@staticmethod
def to_action(n):
return Actions.hit if n==0 else Actions.stick
@staticmethod
def as_int(a):
return 0 if a == Actions.hit else 1
class Environment:
def __init__(self):
self.player_values_count = 21
self.dealer_values_count = 10
self.actions_count = 2 # number of possible actions
def get_start_state(self):
s = State(Card(True), Card(True))
return s
def step(self, s, a):
# type: (object, object) -> object
"""
:type s: State
"""
next_s = copy.copy(s)
r = 0
if a == Actions.stick:
while not next_s.term:
next_s.dealer += Card().value
if next_s.dealer < 1 or next_s.dealer > 21:
next_s.term = True
r = 1
elif next_s.dealer >= 17:
next_s.term = True
if next_s.dealer > next_s.player:
r = -1
elif next_s.dealer < next_s.player:
r = 1
else:
next_s.player += Card().value
if next_s.player < 1 or next_s.player > 21:
next_s.term = True
r = -1
next_s.r = r
return next_s, r
| from enum import Enum
import copy
import random
random.seed(1)
class State:
def __init__(self, dealer_card, player_card, is_terminal=False):
"""
:type self.is_terminal: bool
:type self.dealer: int
:type self.player: int
"""
self.dealer = dealer_card.value
self.player = player_card.value
self.term = is_terminal
self.r = 0
class Card:
def __init__(self, force_black=False):
"""
:type self.value: int
"""
self.value = random.randint(1,10)
self.absolute_value = self.value
if force_black or random.randint(1,3) != 1:
self.is_black = True
else:
self.is_black = False
self.value = 0 - self.value
self.is_red = not self.is_black
class Actions(Enum):
# Possible actions
hit = 0
stick = 1
@staticmethod
def to_action(n):
return Actions.hit if n==0 else Actions.stick
@staticmethod
def as_int(a):
return 0 if a == Actions.hit else 1
class Environment:
def __init__(self):
self.player_values_count = 21
self.dealer_values_count = 10
self.actions_count = 2 # number of possible actions
def get_start_state(self):
s = State(Card(True), Card(True))
return s
def step(self, s, a):
# type: (object, object) -> object
"""
:type s: State
"""
next_s = copy.copy(s)
r = 0
if a == Actions.stick:
while not next_s.term:
next_s.dealer += Card().value
if next_s.dealer < 1 or next_s.dealer > 21:
next_s.term = True
r = 1
elif next_s.dealer >= 17:
next_s.term = True
if next_s.dealer > next_s.player:
r = -1
elif next_s.dealer < next_s.player:
r = 1
else:
next_s.player += Card().value
if next_s.player < 1 or next_s.player > 21:
next_s.term = True
r = -1
next_s.r = r
return next_s, r
| en | 0.47446 | :type self.is_terminal: bool :type self.dealer: int :type self.player: int :type self.value: int # Possible actions # number of possible actions # type: (object, object) -> object :type s: State | 3.447471 | 3 |
tasks/cv-fast-autocv/finetuning.py | vitoryeso/tasks | 2 | 6620629 | <filename>tasks/cv-fast-autocv/finetuning.py
from checkpoint import TrainedModels
from networks import CustomModule
class FineTuning():
def __init__(self, model_archs, num_classes):
self.model_archs = model_archs
self.num_classes = num_classes
self.trained_models = TrainedModels()
def fine_tuning(self, model_arch):
if model_arch in ['resnet18', 'resnet50']:
model_conv = self.trained_models.get_model(model_arch)
for param in model_conv.parameters():
param.requires_grad = False
num_ftrs = model_conv.fc.in_features
net_out = CustomModule(num_ftrs, self.num_classes)
model_conv.fc = net_out
if model_arch in ['vgg16']:
model_conv = self.trained_models.get_model(model_arch)
for param in model_conv.parameters():
param.requires_grad = False
num_ftrs = model_conv.classifier[0].in_features
net_out = CustomModule(num_ftrs, self.num_classes)
model_conv.classifier = net_out
return model_conv
| <filename>tasks/cv-fast-autocv/finetuning.py
from checkpoint import TrainedModels
from networks import CustomModule
class FineTuning():
def __init__(self, model_archs, num_classes):
self.model_archs = model_archs
self.num_classes = num_classes
self.trained_models = TrainedModels()
def fine_tuning(self, model_arch):
if model_arch in ['resnet18', 'resnet50']:
model_conv = self.trained_models.get_model(model_arch)
for param in model_conv.parameters():
param.requires_grad = False
num_ftrs = model_conv.fc.in_features
net_out = CustomModule(num_ftrs, self.num_classes)
model_conv.fc = net_out
if model_arch in ['vgg16']:
model_conv = self.trained_models.get_model(model_arch)
for param in model_conv.parameters():
param.requires_grad = False
num_ftrs = model_conv.classifier[0].in_features
net_out = CustomModule(num_ftrs, self.num_classes)
model_conv.classifier = net_out
return model_conv
| none | 1 | 2.418703 | 2 | |
tests/functional/test_validate.py | KOSASIH/submanager | 2 | 6620630 | <reponame>KOSASIH/submanager
"""Test that the validate-config command validates the configuration."""
# Future imports
from __future__ import (
annotations,
)
# Standard library imports
from typing import (
Dict,
Optional,
Tuple,
Type,
Union,
)
# Third party imports
import pytest
from typing_extensions import (
Final,
)
# Local imports
import submanager.enums
import submanager.exceptions
import submanager.models.config
from submanager.types import (
ConfigDict,
)
from tests.functional.conftest import (
CONFIG_EXTENSIONS_BAD,
CONFIG_EXTENSIONS_GOOD,
CONFIG_PATHS_OFFLINE,
CONFIG_PATHS_ONLINE,
RunAndCheckCLICallable,
RunAndCheckDebugCallable,
)
# ---- Types ----
RequestValues = Union[str, bool, None]
RequestTuple = Union[Tuple[ConfigDict, RequestValues], ConfigDict]
ExpectedTuple = Tuple[
str,
Optional[Type[submanager.exceptions.SubManagerUserError]],
]
ParamConfigs = Dict[str, Tuple[RequestTuple, ExpectedTuple]]
# ---- Constants ----
# pylint: disable = consider-using-namedtuple-or-dataclass
PSEUDORANDOM_STRING: Final[str] = "izouashbutyzyep"
INT_VALUE: Final[int] = 42
# CLI constants
VALIDATE_COMMAND: Final[str] = "validate-config"
MINIMAL_ARGS: Final[list[str]] = ["", "--minimal"]
INCLUDE_DISABLED_ARGS: Final[list[str]] = ["", "--include-disabled"]
OFFLINE_ONLY_ARG: Final[str] = "--offline-only"
OFFLINE_ONLY_ARGS: Final = [
OFFLINE_ONLY_ARG,
pytest.param("", marks=[pytest.mark.online]),
]
OFFLINE_ONLY_ARGS_SLOW: Final = [
OFFLINE_ONLY_ARG,
pytest.param("", marks=[pytest.mark.slow, pytest.mark.online]),
]
# Offline validation param configs
VALIDATION_EXPECTED: Final[ExpectedTuple] = (
"validat",
submanager.exceptions.ConfigValidationError,
)
ACCOUNT_EXPECTED: Final[ExpectedTuple] = (
"account",
submanager.exceptions.AccountConfigError,
)
READONLY_EXPECTED: Final[ExpectedTuple] = (
"read",
submanager.exceptions.RedditReadOnlyError,
)
BAD_VALIDATE_OFFLINE_PARAMS: Final[ParamConfigs] = {
"non_existent_key": (
{PSEUDORANDOM_STRING: PSEUDORANDOM_STRING},
VALIDATION_EXPECTED,
),
"account_int": (
{"context_default": {"account": INT_VALUE}},
VALIDATION_EXPECTED,
),
"account_nomatch": (
{"context_default": {"account": PSEUDORANDOM_STRING}},
VALIDATION_EXPECTED,
),
"subreddit_int": (
{"context_default": {"subreddit": INT_VALUE}},
VALIDATION_EXPECTED,
),
"subreddit_missing": (
{"context_default": {"subreddit": None}},
VALIDATION_EXPECTED,
),
"clientid_missing": (
{"accounts": {"muskbot": {"config": {"client_id": None}}}},
ACCOUNT_EXPECTED,
),
"sitename_nomatch": (
{
"accounts": {
"muskrat": {"config": {"site_name": PSEUDORANDOM_STRING}},
},
},
ACCOUNT_EXPECTED,
),
"token_missing": (
{"accounts": {"muskbot": {"config": {"refresh_token": None}}}},
READONLY_EXPECTED,
),
"pw_missing": (
{"accounts": {"muskrat": {"config": {"password": None}}}},
READONLY_EXPECTED,
),
}
# Onlne validation param configs
NON_ACCESSIBLE_PAGE: Final[str] = "non_accessible_page"
NON_MOD_SUBREDDIT: Final[str] = "SubManagerTesting2"
NON_SUPPORTED_WIDGET: Final[str] = "Bad Type Widget"
NON_WRITEABLE_PAGE: Final[str] = "non_writable_page"
NON_WRITEABLE_WIDGET: Final[str] = "Test Widget"
THREAD_ID_LINK: Final[str] = "oy6ju3"
THREAD_ID_NOT_OP: Final[str] = "owu3jn"
BAD_VALIDATE_ONLINE_PARAMS: Final[ParamConfigs] = {
"placebo": (
({}, True),
("succe", None),
),
"client_id_bad": (
(
{
"accounts": {
"testbot": {"config": {"client_id": PSEUDORANDOM_STRING}},
},
},
True,
),
("scope", submanager.exceptions.ScopeCheckError),
),
"subreddit_notfound": (
(
{"context_default": {"subreddit": PSEUDORANDOM_STRING}},
"sync_manager.items.menus.targets.old_reddit_menu",
),
("subreddit", submanager.exceptions.SubredditNotFoundError),
),
"thread_source_notfound": (
(
{
"thread_manager": {
"items": {
"cycle_thread": {
"source": {"endpoint_name": PSEUDORANDOM_STRING},
},
},
},
},
"thread_manager.items.cycle_thread",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"menu_notfound": (
(
{
"sync_manager": {
"items": {
"menus": {
"targets": {
"new_reddit_menu": {
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.menus.targets.new_reddit_menu",
),
("create", submanager.exceptions.RedditObjectNotFoundError),
),
"thread_notfound": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"thread_notop": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": THREAD_ID_NOT_OP,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("account", submanager.exceptions.NotOPError),
),
"thread_wrong_type": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": THREAD_ID_LINK,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("link", submanager.exceptions.PostTypeError),
),
"widget_notfound": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"widget_wrong_type": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": NON_SUPPORTED_WIDGET,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("type", submanager.exceptions.WidgetTypeError),
),
"widget_notwriteable": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": NON_WRITEABLE_WIDGET,
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("mod", submanager.exceptions.NotAModError),
),
"wiki_notfound_source": (
(
{
"sync_manager": {
"items": {
"cross_sub_sync": {
"source": {"endpoint_name": PSEUDORANDOM_STRING},
},
},
},
},
"sync_manager.items.cross_sub_sync.targets.index_clone",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"wiki_notaccessible_source": (
(
{
"sync_manager": {
"items": {
"cross_sub_sync": {
"source": {"endpoint_name": NON_ACCESSIBLE_PAGE},
},
},
},
},
"sync_manager.items.cross_sub_sync.targets.index_clone",
),
("access", submanager.exceptions.RedditObjectNotAccessibleError),
),
"wiki_notfound_target": (
(
{
"sync_manager": {
"items": {
"disabled_sync_item": {
"targets": {
"non_existent": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"wiki_notaccessible_target": (
(
{},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("access", submanager.exceptions.RedditObjectNotAccessibleError),
),
"wiki_notwriteable_target": (
(
{
"sync_manager": {
"items": {
"disabled_sync_item": {
"targets": {
"non_existent": {
"endpoint_name": NON_WRITEABLE_PAGE,
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("edit", submanager.exceptions.WikiPagePermissionError),
),
}
# ---- Tests ----
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
def test_generated_error(
run_and_check_cli: RunAndCheckCLICallable,
example_config: submanager.models.config.ConfigPaths,
minimal: str,
include_disabled: str,
) -> None:
"""Test that the generated config validates false."""
error_type: type[submanager.exceptions.SubManagerUserError]
if minimal:
error_type = submanager.exceptions.AccountConfigError
else:
error_type = submanager.exceptions.ConfigDefaultError
run_and_check_cli(
cli_args=[
VALIDATE_COMMAND,
OFFLINE_ONLY_ARG,
minimal,
include_disabled,
],
config_paths=example_config,
check_text="account" if minimal else "default",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=error_type,
)
@pytest.mark.parametrize("temp_config_dir", ["", "missing_dir"], indirect=True)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
def test_config_not_found(
run_and_check_cli: RunAndCheckCLICallable,
temp_config_paths: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that the config not being found validates false."""
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=temp_config_paths,
check_text="not found",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigNotFoundError,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize(
"temp_config_paths",
CONFIG_EXTENSIONS_GOOD + CONFIG_EXTENSIONS_BAD,
indirect=True,
)
def test_config_empty_error(
run_and_check_cli: RunAndCheckCLICallable,
empty_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that validating a config file with an unknown extension errors."""
extension = empty_config.static.suffix.lstrip(".")
check_error: type[submanager.exceptions.SubManagerUserError]
if extension == "json":
check_text = "pars"
check_error = submanager.exceptions.ConfigParsingError
elif extension in CONFIG_EXTENSIONS_GOOD:
check_text = "empty"
check_error = submanager.exceptions.ConfigEmptyError
else:
check_text = "extension"
check_error = submanager.exceptions.ConfigExtensionError
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=empty_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("temp_config_paths", ["json"], indirect=True)
def test_config_list_error(
run_and_check_cli: RunAndCheckCLICallable,
list_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that a config file with the wrong data structure fails validate."""
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=list_config,
check_text="structure",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigDataTypeError,
)
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_valid_offline(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
minimal: str,
include_disabled: str,
) -> None:
"""Test that the test configs validate true in offline mode."""
run_and_check_cli(
cli_args=[
VALIDATE_COMMAND,
OFFLINE_ONLY_ARG,
minimal,
include_disabled,
],
config_paths=file_config,
check_text="succe",
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_parsing_error(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that config files with an invalid file format validate false."""
with open(file_config.static, encoding="utf-8") as config_file_read:
config_file_text = config_file_read.read()
config_file_text = config_file_text.replace('"', "", 1)
with open(
file_config.static,
mode="w",
encoding="utf-8",
newline="\n",
) as config_file_write:
config_file_write.write(config_file_text)
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=file_config,
check_text="pars",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigParsingError,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize(
("modified_config", "check_vars"),
list(BAD_VALIDATE_OFFLINE_PARAMS.values()),
ids=list(BAD_VALIDATE_OFFLINE_PARAMS.keys()),
indirect=["modified_config"],
)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_value_error(
run_and_check_cli: RunAndCheckCLICallable,
modified_config: submanager.models.config.ConfigPaths,
check_vars: ExpectedTuple,
minimal: str,
) -> None:
"""Test that config files with a bad value validate false."""
check_text, check_error = check_vars
cli_args = [VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal]
if minimal and (
check_error is None
or (check_error == submanager.exceptions.RedditReadOnlyError)
):
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text="succe",
)
else:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
)
def test_debug_error(
run_and_check_debug: RunAndCheckDebugCallable,
) -> None:
"""Test that --debug allows the error to bubble up and dump traceback."""
run_and_check_debug([VALIDATE_COMMAND, OFFLINE_ONLY_ARG])
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("offline_only", OFFLINE_ONLY_ARGS_SLOW)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_ONLINE, indirect=True)
def test_valid_online(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
offline_only: str,
include_disabled: str,
) -> None:
"""Test that the test configs validate true in offline mode."""
should_fail = bool(include_disabled and not offline_only)
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, offline_only, include_disabled],
config_paths=file_config,
check_text="access" if should_fail else "succe",
check_exits=should_fail,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.RedditObjectNotAccessibleError,
)
@pytest.mark.parametrize("offline_only", OFFLINE_ONLY_ARGS)
@pytest.mark.parametrize(
("modified_config", "check_vars"),
list(BAD_VALIDATE_ONLINE_PARAMS.values()),
ids=list(BAD_VALIDATE_ONLINE_PARAMS.keys()),
indirect=["modified_config"],
)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_ONLINE, indirect=True)
def test_online_error(
run_and_check_cli: RunAndCheckCLICallable,
modified_config: submanager.models.config.ConfigPaths,
check_vars: ExpectedTuple,
offline_only: str,
) -> None:
"""Test that config files that produce Reddit errors validate false."""
check_text, check_error = check_vars
cli_args = [VALIDATE_COMMAND, offline_only]
if offline_only or check_error is None:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text="succe",
)
else:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
)
| """Test that the validate-config command validates the configuration."""
# Future imports
from __future__ import (
annotations,
)
# Standard library imports
from typing import (
Dict,
Optional,
Tuple,
Type,
Union,
)
# Third party imports
import pytest
from typing_extensions import (
Final,
)
# Local imports
import submanager.enums
import submanager.exceptions
import submanager.models.config
from submanager.types import (
ConfigDict,
)
from tests.functional.conftest import (
CONFIG_EXTENSIONS_BAD,
CONFIG_EXTENSIONS_GOOD,
CONFIG_PATHS_OFFLINE,
CONFIG_PATHS_ONLINE,
RunAndCheckCLICallable,
RunAndCheckDebugCallable,
)
# ---- Types ----
RequestValues = Union[str, bool, None]
RequestTuple = Union[Tuple[ConfigDict, RequestValues], ConfigDict]
ExpectedTuple = Tuple[
str,
Optional[Type[submanager.exceptions.SubManagerUserError]],
]
ParamConfigs = Dict[str, Tuple[RequestTuple, ExpectedTuple]]
# ---- Constants ----
# pylint: disable = consider-using-namedtuple-or-dataclass
PSEUDORANDOM_STRING: Final[str] = "izouashbutyzyep"
INT_VALUE: Final[int] = 42
# CLI constants
VALIDATE_COMMAND: Final[str] = "validate-config"
MINIMAL_ARGS: Final[list[str]] = ["", "--minimal"]
INCLUDE_DISABLED_ARGS: Final[list[str]] = ["", "--include-disabled"]
OFFLINE_ONLY_ARG: Final[str] = "--offline-only"
OFFLINE_ONLY_ARGS: Final = [
OFFLINE_ONLY_ARG,
pytest.param("", marks=[pytest.mark.online]),
]
OFFLINE_ONLY_ARGS_SLOW: Final = [
OFFLINE_ONLY_ARG,
pytest.param("", marks=[pytest.mark.slow, pytest.mark.online]),
]
# Offline validation param configs
VALIDATION_EXPECTED: Final[ExpectedTuple] = (
"validat",
submanager.exceptions.ConfigValidationError,
)
ACCOUNT_EXPECTED: Final[ExpectedTuple] = (
"account",
submanager.exceptions.AccountConfigError,
)
READONLY_EXPECTED: Final[ExpectedTuple] = (
"read",
submanager.exceptions.RedditReadOnlyError,
)
BAD_VALIDATE_OFFLINE_PARAMS: Final[ParamConfigs] = {
"non_existent_key": (
{PSEUDORANDOM_STRING: PSEUDORANDOM_STRING},
VALIDATION_EXPECTED,
),
"account_int": (
{"context_default": {"account": INT_VALUE}},
VALIDATION_EXPECTED,
),
"account_nomatch": (
{"context_default": {"account": PSEUDORANDOM_STRING}},
VALIDATION_EXPECTED,
),
"subreddit_int": (
{"context_default": {"subreddit": INT_VALUE}},
VALIDATION_EXPECTED,
),
"subreddit_missing": (
{"context_default": {"subreddit": None}},
VALIDATION_EXPECTED,
),
"clientid_missing": (
{"accounts": {"muskbot": {"config": {"client_id": None}}}},
ACCOUNT_EXPECTED,
),
"sitename_nomatch": (
{
"accounts": {
"muskrat": {"config": {"site_name": PSEUDORANDOM_STRING}},
},
},
ACCOUNT_EXPECTED,
),
"token_missing": (
{"accounts": {"muskbot": {"config": {"refresh_token": None}}}},
READONLY_EXPECTED,
),
"pw_missing": (
{"accounts": {"muskrat": {"config": {"password": None}}}},
READONLY_EXPECTED,
),
}
# Onlne validation param configs
NON_ACCESSIBLE_PAGE: Final[str] = "non_accessible_page"
NON_MOD_SUBREDDIT: Final[str] = "SubManagerTesting2"
NON_SUPPORTED_WIDGET: Final[str] = "Bad Type Widget"
NON_WRITEABLE_PAGE: Final[str] = "non_writable_page"
NON_WRITEABLE_WIDGET: Final[str] = "Test Widget"
THREAD_ID_LINK: Final[str] = "oy6ju3"
THREAD_ID_NOT_OP: Final[str] = "owu3jn"
BAD_VALIDATE_ONLINE_PARAMS: Final[ParamConfigs] = {
"placebo": (
({}, True),
("succe", None),
),
"client_id_bad": (
(
{
"accounts": {
"testbot": {"config": {"client_id": PSEUDORANDOM_STRING}},
},
},
True,
),
("scope", submanager.exceptions.ScopeCheckError),
),
"subreddit_notfound": (
(
{"context_default": {"subreddit": PSEUDORANDOM_STRING}},
"sync_manager.items.menus.targets.old_reddit_menu",
),
("subreddit", submanager.exceptions.SubredditNotFoundError),
),
"thread_source_notfound": (
(
{
"thread_manager": {
"items": {
"cycle_thread": {
"source": {"endpoint_name": PSEUDORANDOM_STRING},
},
},
},
},
"thread_manager.items.cycle_thread",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"menu_notfound": (
(
{
"sync_manager": {
"items": {
"menus": {
"targets": {
"new_reddit_menu": {
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.menus.targets.new_reddit_menu",
),
("create", submanager.exceptions.RedditObjectNotFoundError),
),
"thread_notfound": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"thread_notop": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": THREAD_ID_NOT_OP,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("account", submanager.exceptions.NotOPError),
),
"thread_wrong_type": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"thread_target": {
"endpoint_name": THREAD_ID_LINK,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.thread_target",
),
("link", submanager.exceptions.PostTypeError),
),
"widget_notfound": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"widget_wrong_type": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": NON_SUPPORTED_WIDGET,
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("type", submanager.exceptions.WidgetTypeError),
),
"widget_notwriteable": (
(
{
"sync_manager": {
"items": {
"sidebar_thread": {
"targets": {
"new_reddit_widget": {
"endpoint_name": NON_WRITEABLE_WIDGET,
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.sidebar_thread.targets.new_reddit_widget",
),
("mod", submanager.exceptions.NotAModError),
),
"wiki_notfound_source": (
(
{
"sync_manager": {
"items": {
"cross_sub_sync": {
"source": {"endpoint_name": PSEUDORANDOM_STRING},
},
},
},
},
"sync_manager.items.cross_sub_sync.targets.index_clone",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"wiki_notaccessible_source": (
(
{
"sync_manager": {
"items": {
"cross_sub_sync": {
"source": {"endpoint_name": NON_ACCESSIBLE_PAGE},
},
},
},
},
"sync_manager.items.cross_sub_sync.targets.index_clone",
),
("access", submanager.exceptions.RedditObjectNotAccessibleError),
),
"wiki_notfound_target": (
(
{
"sync_manager": {
"items": {
"disabled_sync_item": {
"targets": {
"non_existent": {
"endpoint_name": PSEUDORANDOM_STRING,
},
},
},
},
},
},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("found", submanager.exceptions.RedditObjectNotFoundError),
),
"wiki_notaccessible_target": (
(
{},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("access", submanager.exceptions.RedditObjectNotAccessibleError),
),
"wiki_notwriteable_target": (
(
{
"sync_manager": {
"items": {
"disabled_sync_item": {
"targets": {
"non_existent": {
"endpoint_name": NON_WRITEABLE_PAGE,
"context": {
"subreddit": NON_MOD_SUBREDDIT,
},
},
},
},
},
},
},
"sync_manager.items.disabled_sync_item.targets.non_existent",
),
("edit", submanager.exceptions.WikiPagePermissionError),
),
}
# ---- Tests ----
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
def test_generated_error(
run_and_check_cli: RunAndCheckCLICallable,
example_config: submanager.models.config.ConfigPaths,
minimal: str,
include_disabled: str,
) -> None:
"""Test that the generated config validates false."""
error_type: type[submanager.exceptions.SubManagerUserError]
if minimal:
error_type = submanager.exceptions.AccountConfigError
else:
error_type = submanager.exceptions.ConfigDefaultError
run_and_check_cli(
cli_args=[
VALIDATE_COMMAND,
OFFLINE_ONLY_ARG,
minimal,
include_disabled,
],
config_paths=example_config,
check_text="account" if minimal else "default",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=error_type,
)
@pytest.mark.parametrize("temp_config_dir", ["", "missing_dir"], indirect=True)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
def test_config_not_found(
run_and_check_cli: RunAndCheckCLICallable,
temp_config_paths: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that the config not being found validates false."""
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=temp_config_paths,
check_text="not found",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigNotFoundError,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize(
"temp_config_paths",
CONFIG_EXTENSIONS_GOOD + CONFIG_EXTENSIONS_BAD,
indirect=True,
)
def test_config_empty_error(
run_and_check_cli: RunAndCheckCLICallable,
empty_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that validating a config file with an unknown extension errors."""
extension = empty_config.static.suffix.lstrip(".")
check_error: type[submanager.exceptions.SubManagerUserError]
if extension == "json":
check_text = "pars"
check_error = submanager.exceptions.ConfigParsingError
elif extension in CONFIG_EXTENSIONS_GOOD:
check_text = "empty"
check_error = submanager.exceptions.ConfigEmptyError
else:
check_text = "extension"
check_error = submanager.exceptions.ConfigExtensionError
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=empty_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("temp_config_paths", ["json"], indirect=True)
def test_config_list_error(
run_and_check_cli: RunAndCheckCLICallable,
list_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that a config file with the wrong data structure fails validate."""
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=list_config,
check_text="structure",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigDataTypeError,
)
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_valid_offline(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
minimal: str,
include_disabled: str,
) -> None:
"""Test that the test configs validate true in offline mode."""
run_and_check_cli(
cli_args=[
VALIDATE_COMMAND,
OFFLINE_ONLY_ARG,
minimal,
include_disabled,
],
config_paths=file_config,
check_text="succe",
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_parsing_error(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
minimal: str,
) -> None:
"""Test that config files with an invalid file format validate false."""
with open(file_config.static, encoding="utf-8") as config_file_read:
config_file_text = config_file_read.read()
config_file_text = config_file_text.replace('"', "", 1)
with open(
file_config.static,
mode="w",
encoding="utf-8",
newline="\n",
) as config_file_write:
config_file_write.write(config_file_text)
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal],
config_paths=file_config,
check_text="pars",
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.ConfigParsingError,
)
@pytest.mark.parametrize("minimal", MINIMAL_ARGS)
@pytest.mark.parametrize(
("modified_config", "check_vars"),
list(BAD_VALIDATE_OFFLINE_PARAMS.values()),
ids=list(BAD_VALIDATE_OFFLINE_PARAMS.keys()),
indirect=["modified_config"],
)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_OFFLINE, indirect=True)
def test_value_error(
run_and_check_cli: RunAndCheckCLICallable,
modified_config: submanager.models.config.ConfigPaths,
check_vars: ExpectedTuple,
minimal: str,
) -> None:
"""Test that config files with a bad value validate false."""
check_text, check_error = check_vars
cli_args = [VALIDATE_COMMAND, OFFLINE_ONLY_ARG, minimal]
if minimal and (
check_error is None
or (check_error == submanager.exceptions.RedditReadOnlyError)
):
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text="succe",
)
else:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
)
def test_debug_error(
run_and_check_debug: RunAndCheckDebugCallable,
) -> None:
"""Test that --debug allows the error to bubble up and dump traceback."""
run_and_check_debug([VALIDATE_COMMAND, OFFLINE_ONLY_ARG])
@pytest.mark.parametrize("include_disabled", INCLUDE_DISABLED_ARGS)
@pytest.mark.parametrize("offline_only", OFFLINE_ONLY_ARGS_SLOW)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_ONLINE, indirect=True)
def test_valid_online(
run_and_check_cli: RunAndCheckCLICallable,
file_config: submanager.models.config.ConfigPaths,
offline_only: str,
include_disabled: str,
) -> None:
"""Test that the test configs validate true in offline mode."""
should_fail = bool(include_disabled and not offline_only)
run_and_check_cli(
cli_args=[VALIDATE_COMMAND, offline_only, include_disabled],
config_paths=file_config,
check_text="access" if should_fail else "succe",
check_exits=should_fail,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=submanager.exceptions.RedditObjectNotAccessibleError,
)
@pytest.mark.parametrize("offline_only", OFFLINE_ONLY_ARGS)
@pytest.mark.parametrize(
("modified_config", "check_vars"),
list(BAD_VALIDATE_ONLINE_PARAMS.values()),
ids=list(BAD_VALIDATE_ONLINE_PARAMS.keys()),
indirect=["modified_config"],
)
@pytest.mark.parametrize("file_config", CONFIG_PATHS_ONLINE, indirect=True)
def test_online_error(
run_and_check_cli: RunAndCheckCLICallable,
modified_config: submanager.models.config.ConfigPaths,
check_vars: ExpectedTuple,
offline_only: str,
) -> None:
"""Test that config files that produce Reddit errors validate false."""
check_text, check_error = check_vars
cli_args = [VALIDATE_COMMAND, offline_only]
if offline_only or check_error is None:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text="succe",
)
else:
run_and_check_cli(
cli_args=cli_args,
config_paths=modified_config,
check_text=check_text,
check_code=submanager.enums.ExitCode.ERROR_USER,
check_error=check_error,
) | en | 0.647872 | Test that the validate-config command validates the configuration. # Future imports # Standard library imports # Third party imports # Local imports # ---- Types ---- # ---- Constants ---- # pylint: disable = consider-using-namedtuple-or-dataclass # CLI constants # Offline validation param configs # Onlne validation param configs # ---- Tests ---- Test that the generated config validates false. Test that the config not being found validates false. Test that validating a config file with an unknown extension errors. Test that a config file with the wrong data structure fails validate. Test that the test configs validate true in offline mode. Test that config files with an invalid file format validate false. Test that config files with a bad value validate false. Test that --debug allows the error to bubble up and dump traceback. Test that the test configs validate true in offline mode. Test that config files that produce Reddit errors validate false. | 2.058074 | 2 |
demos/prey-predator/run.py | calvbore/demos | 1 | 6620631 | <filename>demos/prey-predator/run.py
# The following imports NEED to be in the exact order
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
# Simulation configs, input any new simulations here
from prey_predator_sd import config
from prey_predator_abm import config
#from {new_simulation} import config
from cadCAD import configs
import pandas as pd
def run(drop_midsteps: bool=True) -> pd.DataFrame:
"""
Run all experiments and return their output on the dataset column.
Each line represents an iteration of the parameter-sweep combinations.
"""
exec_mode = ExecutionMode()
exec_context = ExecutionContext(exec_mode.local_mode)
run = Executor(exec_context=exec_context, configs=configs)
results = pd.DataFrame()
(system_events, tensor_field, sessions) = run.execute()
df = pd.DataFrame(system_events)
results = []
for i, (_, subset_df) in enumerate(df.groupby(["simulation", "subset"])):
params = configs[i].sim_config['M']
result_record = pd.DataFrame.from_records([tuple([i for i in params.values()])], columns=list(params.keys()))
# keep only last substep of each timestep
if drop_midsteps:
max_substep = max(subset_df.substep)
is_droppable = (subset_df.substep != max_substep)
is_droppable &= (subset_df.substep != 0)
subset_df = subset_df.loc[~is_droppable]
result_record['dataset'] = [subset_df]
results.append(result_record)
return pd.concat(results).reset_index() | <filename>demos/prey-predator/run.py
# The following imports NEED to be in the exact order
from cadCAD.engine import ExecutionMode, ExecutionContext, Executor
# Simulation configs, input any new simulations here
from prey_predator_sd import config
from prey_predator_abm import config
#from {new_simulation} import config
from cadCAD import configs
import pandas as pd
def run(drop_midsteps: bool=True) -> pd.DataFrame:
"""
Run all experiments and return their output on the dataset column.
Each line represents an iteration of the parameter-sweep combinations.
"""
exec_mode = ExecutionMode()
exec_context = ExecutionContext(exec_mode.local_mode)
run = Executor(exec_context=exec_context, configs=configs)
results = pd.DataFrame()
(system_events, tensor_field, sessions) = run.execute()
df = pd.DataFrame(system_events)
results = []
for i, (_, subset_df) in enumerate(df.groupby(["simulation", "subset"])):
params = configs[i].sim_config['M']
result_record = pd.DataFrame.from_records([tuple([i for i in params.values()])], columns=list(params.keys()))
# keep only last substep of each timestep
if drop_midsteps:
max_substep = max(subset_df.substep)
is_droppable = (subset_df.substep != max_substep)
is_droppable &= (subset_df.substep != 0)
subset_df = subset_df.loc[~is_droppable]
result_record['dataset'] = [subset_df]
results.append(result_record)
return pd.concat(results).reset_index() | en | 0.727511 | # The following imports NEED to be in the exact order # Simulation configs, input any new simulations here #from {new_simulation} import config Run all experiments and return their output on the dataset column. Each line represents an iteration of the parameter-sweep combinations. # keep only last substep of each timestep | 2.316818 | 2 |
sequentialSearch.py | adenosinew/algorithms | 0 | 6620632 | <reponame>adenosinew/algorithms<filename>sequentialSearch.py
def sequentialSearch(alist, item):
pos = 0
found = False
while pos < len(alist) and not found:
if alist[pos] == item:
found = True
else:
pos = pos + 1
return found
testlist = [1,2,3,4,8,32,35,14,6,0]
print(sequentialSearch(testlist, 3))
| def sequentialSearch(alist, item):
pos = 0
found = False
while pos < len(alist) and not found:
if alist[pos] == item:
found = True
else:
pos = pos + 1
return found
testlist = [1,2,3,4,8,32,35,14,6,0]
print(sequentialSearch(testlist, 3)) | none | 1 | 3.922633 | 4 | |
utils/json_aggregator.py | eolecvk/intro_spark_twitter | 1 | 6620633 | <reponame>eolecvk/intro_spark_twitter
def jsonfiles_to_json(indir_path, outfile_path):
"""
Group a collection of json objects in individividual files into a single json file,
one line per json object
cf https://docs.databricks.com/spark/latest/data-sources/read-json.html
"""
import os
import simplejson as json
# Generate list of tweet file full paths
fpaths = [os.path.join(indir_path, fname) for fname in os.listdir(indir_path)]
# Define list of tweets to write in output file
result = []
# Open each tweet file and get relevant fields
for fpath in fpaths:
try:
with open(fpath, 'r') as fp:
tweet = json.load(fp)
tweet_id = tweet['id']
user_id = tweet['user']['id']
text = (tweet['text']
.replace('\n',' ')
.replace('\t',' ')
.replace('\r',' ')
.replace('"',' '))
new_record = {
"tweet_id" : tweet_id,
"user_id" : user_id,
"text" : text
}
new_record_str = json.dumps(new_record, separators=(',', ':'))
result.append(new_record_str)
except Exception as e:
print(e)
continue
# Write list of json objects to file (one obj per line)
with open(outfile_path, 'w') as fp:
for line in result:
fp.write(line + '\n')
def jsonfiles_to_csv(dirpath, tsvpath):
"""
inputs:
+ dirpath : full path of dir that contains the tweets .json file
+ csvpath : full path of output tsv file
Compiles a collection of tweets as a tsv file.
The tweet fields that are kept include: `user_id`, `tweet_id`, and `tweet_text`
"""
import os
import csv
# Generate list of tweet file full paths
fpaths = [os.path.join(dirpath, fname) for fname in os.listdir(dirpath)]
# Define result list (to be written to output file)
result = []
# Open each tweet file and get relevant fields
for fpath in fpaths:
try:
with open(fpath, 'r') as fp:
tweet = json.load(fp)
tweet_id = tweet['id']
user_id = tweet['user']['id']
text = (tweet['text']
.replace('\n',' ')
.replace('\t',' ')
.replace('\r',' ')
.replace('"',' '))
new_record = (tweet_id, user_id, text)
result.append(new_record)
except Exception as e:
print(e)
print("Issue with file: [{}]".format(fpath))
# Save output to .tsv file
with open(tsvpath, 'w') as fp:
wr = csv.writer(fp, delimiter='\t')
wr.writerows(result)
# -----------------------------------------------------------------------
if __name__ == "__main__":
dirpath = "FULL/PATH/TO/INPUT/TWEET/DIR"
outpath = "FULL/PATH/TO/OUTPUT/JSON/FILE"
jsonfiles_to_json(dirpath, outpath) | def jsonfiles_to_json(indir_path, outfile_path):
"""
Group a collection of json objects in individividual files into a single json file,
one line per json object
cf https://docs.databricks.com/spark/latest/data-sources/read-json.html
"""
import os
import simplejson as json
# Generate list of tweet file full paths
fpaths = [os.path.join(indir_path, fname) for fname in os.listdir(indir_path)]
# Define list of tweets to write in output file
result = []
# Open each tweet file and get relevant fields
for fpath in fpaths:
try:
with open(fpath, 'r') as fp:
tweet = json.load(fp)
tweet_id = tweet['id']
user_id = tweet['user']['id']
text = (tweet['text']
.replace('\n',' ')
.replace('\t',' ')
.replace('\r',' ')
.replace('"',' '))
new_record = {
"tweet_id" : tweet_id,
"user_id" : user_id,
"text" : text
}
new_record_str = json.dumps(new_record, separators=(',', ':'))
result.append(new_record_str)
except Exception as e:
print(e)
continue
# Write list of json objects to file (one obj per line)
with open(outfile_path, 'w') as fp:
for line in result:
fp.write(line + '\n')
def jsonfiles_to_csv(dirpath, tsvpath):
"""
inputs:
+ dirpath : full path of dir that contains the tweets .json file
+ csvpath : full path of output tsv file
Compiles a collection of tweets as a tsv file.
The tweet fields that are kept include: `user_id`, `tweet_id`, and `tweet_text`
"""
import os
import csv
# Generate list of tweet file full paths
fpaths = [os.path.join(dirpath, fname) for fname in os.listdir(dirpath)]
# Define result list (to be written to output file)
result = []
# Open each tweet file and get relevant fields
for fpath in fpaths:
try:
with open(fpath, 'r') as fp:
tweet = json.load(fp)
tweet_id = tweet['id']
user_id = tweet['user']['id']
text = (tweet['text']
.replace('\n',' ')
.replace('\t',' ')
.replace('\r',' ')
.replace('"',' '))
new_record = (tweet_id, user_id, text)
result.append(new_record)
except Exception as e:
print(e)
print("Issue with file: [{}]".format(fpath))
# Save output to .tsv file
with open(tsvpath, 'w') as fp:
wr = csv.writer(fp, delimiter='\t')
wr.writerows(result)
# -----------------------------------------------------------------------
if __name__ == "__main__":
dirpath = "FULL/PATH/TO/INPUT/TWEET/DIR"
outpath = "FULL/PATH/TO/OUTPUT/JSON/FILE"
jsonfiles_to_json(dirpath, outpath) | en | 0.708111 | Group a collection of json objects in individividual files into a single json file, one line per json object cf https://docs.databricks.com/spark/latest/data-sources/read-json.html # Generate list of tweet file full paths # Define list of tweets to write in output file # Open each tweet file and get relevant fields # Write list of json objects to file (one obj per line) inputs: + dirpath : full path of dir that contains the tweets .json file + csvpath : full path of output tsv file Compiles a collection of tweets as a tsv file. The tweet fields that are kept include: `user_id`, `tweet_id`, and `tweet_text` # Generate list of tweet file full paths # Define result list (to be written to output file) # Open each tweet file and get relevant fields # Save output to .tsv file # ----------------------------------------------------------------------- | 3.453315 | 3 |
src/genie/libs/parser/iosxr/show_media.py | deepB123/genieparser | 0 | 6620634 | <filename>src/genie/libs/parser/iosxr/show_media.py
''' show_media.py
IOSXR parsers for the following show commands:
* 'show media'
* 'show filesystem'
* 'show controllers fabric plane all'
'''
from genie.metaparser import MetaParser
from genie.metaparser.util.schemaengine import Any, Or, Optional
import re
# =======================================================
# Schema for `show media`
# ========================================================
class ShowMediaSchema(MetaParser):
schema = {
'partition': {
Any(): {
'size': str,
'used': str,
'percent': str,
'avail': str,
}
}
}
class ShowMedia(ShowMediaSchema):
"""Parser for show media interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show media'
"""
Tue Apr 13 18:43:17.452 UTC
Media info for node0_RP0_CPU0
------------------------------------------------------------
Partition Size Used Percent Avail
disk2: 3.8G 945M 25% 2.9G
disk0: 3.4G 9.6M 1% 3.2G
/var/lib/docker 5.6G 12M 1% 5.3G
harddisk: 51G 1016M 3% 48G
log: 4.5G 253M 6% 4.0G
------------------------------------------------------------
log: = system log files (read-only)
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
media_dict = {}
result_dict = {}
"""
Variables Parsed:
partition = Partition
size = Size
used = Used
percent = Percent
avail = Avail
"""
p0 = re.compile(r'^(?P<partition>(\w+:|\/\S+))\s+(?P<size>\S+)\s+(?P<used>\S+)\s+(?P<percent>\d+%)\s+(?P<avail>\S+)$')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'partition' not in media_dict:
result_dict = media_dict.setdefault('partition',{})
size = m.groupdict()['size']
used = m.groupdict()['used']
percent = m.groupdict()['percent']
avail = m.groupdict()['avail']
partition = m.groupdict()['partition']
result_dict[partition] = {}
result_dict[partition]['size'] = size
result_dict[partition]['used'] = used
result_dict[partition]['percent'] = percent
result_dict[partition]['avail'] = avail
continue
return media_dict
# ==========================
# Parser for 'show filesystem'
# ==========================
# =======================================================
# Schema for `show filesystem`
# ========================================================
class FileSystemSchema(MetaParser):
schema = {
'prefixes': {
Any(): {
'size': str,
'free': str,
'type': str,
'flags': str,
}
}
}
class ShowFileSystem(FileSystemSchema):
"""Parser for show filesystem interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show filesystem'
"""
Fri Apr 16 21:22:35.610 UTC
File Systems:
Size(b) Free(b) Type Flags Prefixes
48648003584 42960728064 flash rw /misc/config
0 0 network rw tftp:
4008443904 3018457088 flash-disk rw disk2:
0 0 network rw ftp:
54744576000 53680197632 harddisk rw harddisk:
3590602752 3580395520 flash-disk rw disk0:
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
filesystem_dict = {}
result_dict = {}
"""
Variables Parsed:
size = Size
free = Free
type = Type
flags = Flags
prefixes = Prefixes
"""
p0 = re.compile(r'^(?P<size>\s*\d+)\s+(?P<free>\d+)\s+(?P<type>(\w+|\w+-\w+))\s+(?P<flags>\w+)\s+(?P<prefixes>(\w+:|.?\w+)*)')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'prefixes' not in filesystem_dict:
result_dict = filesystem_dict.setdefault('prefixes',{})
size = m.groupdict()['size']
free = m.groupdict()['free']
type_ = m.groupdict()['type']
flags = m.groupdict()['flags']
prefixes = m.groupdict()['prefixes']
result_dict[prefixes] = {}
result_dict[prefixes]['size'] = size
result_dict[prefixes]['free'] = free
result_dict[prefixes]['type'] = type_
result_dict[prefixes]['flags'] = flags
continue
return filesystem_dict
# ==========================
# Parser for 'show controllers fabric plane all'
# ==========================
# =======================================================
# Schema for `show controllers fabric plane all`
# ========================================================
class ControllersFabricPlaneAllSchema(MetaParser):
schema = {
'plane_id': {
Any(): {
'admin_state': str,
'plane_state': str,
'ud_counter': str,
'mcast_counter': str,
}
}
}
class ShowControllersFabricPlaneAll(ControllersFabricPlaneAllSchema):
"""Parser for show controller fabric plane all interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show controllers fabric plane all'
"""
Thu Jul 30 13:16:17.593 UTC
Plane Admin Plane up->dn up->mcast
Id State State counter counter
--------------------------------------
0 UP UP 0 0
1 UP UP 0 0
2 UP DN 0 0
3 UP DN 0 0
4 UP DN 0 0
5 UP DN 0 0
6 UP DN 0 0
7 UP DN 0 0
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
cfabric_dict = {}
result_dict = {}
"""
Variables Parsed:
plane_id = Plane ID
admin_state = Admin State
plane_state = Plane State
ud_counter = up->down counter
mcast_counter = mcast counter
"""
p0 = re.compile(r'^(?P<plane_id>\d+)\s+(?P<admin_state>\w+)\s+(?P<plane_state>\w+)\s+(?P<ud_counter>\d+)\s+(?P<mcast_counter>\d+)')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'plane_id' not in cfabric_dict:
result_dict = cfabric_dict.setdefault('plane_id',{})
plane_id = m.groupdict()['plane_id']
admin_state = m.groupdict()['admin_state']
plane_state = m.groupdict()['plane_state']
ud_counter = m.groupdict()['ud_counter']
mcast_counter = m.groupdict()['mcast_counter']
result_dict[plane_id] = {}
result_dict[plane_id]['admin_state'] = admin_state
result_dict[plane_id]['plane_state'] = plane_state
result_dict[plane_id]['ud_counter'] = ud_counter
result_dict[plane_id]['mcast_counter'] = mcast_counter
continue
return cfabric_dict
| <filename>src/genie/libs/parser/iosxr/show_media.py
''' show_media.py
IOSXR parsers for the following show commands:
* 'show media'
* 'show filesystem'
* 'show controllers fabric plane all'
'''
from genie.metaparser import MetaParser
from genie.metaparser.util.schemaengine import Any, Or, Optional
import re
# =======================================================
# Schema for `show media`
# ========================================================
class ShowMediaSchema(MetaParser):
schema = {
'partition': {
Any(): {
'size': str,
'used': str,
'percent': str,
'avail': str,
}
}
}
class ShowMedia(ShowMediaSchema):
"""Parser for show media interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show media'
"""
Tue Apr 13 18:43:17.452 UTC
Media info for node0_RP0_CPU0
------------------------------------------------------------
Partition Size Used Percent Avail
disk2: 3.8G 945M 25% 2.9G
disk0: 3.4G 9.6M 1% 3.2G
/var/lib/docker 5.6G 12M 1% 5.3G
harddisk: 51G 1016M 3% 48G
log: 4.5G 253M 6% 4.0G
------------------------------------------------------------
log: = system log files (read-only)
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
media_dict = {}
result_dict = {}
"""
Variables Parsed:
partition = Partition
size = Size
used = Used
percent = Percent
avail = Avail
"""
p0 = re.compile(r'^(?P<partition>(\w+:|\/\S+))\s+(?P<size>\S+)\s+(?P<used>\S+)\s+(?P<percent>\d+%)\s+(?P<avail>\S+)$')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'partition' not in media_dict:
result_dict = media_dict.setdefault('partition',{})
size = m.groupdict()['size']
used = m.groupdict()['used']
percent = m.groupdict()['percent']
avail = m.groupdict()['avail']
partition = m.groupdict()['partition']
result_dict[partition] = {}
result_dict[partition]['size'] = size
result_dict[partition]['used'] = used
result_dict[partition]['percent'] = percent
result_dict[partition]['avail'] = avail
continue
return media_dict
# ==========================
# Parser for 'show filesystem'
# ==========================
# =======================================================
# Schema for `show filesystem`
# ========================================================
class FileSystemSchema(MetaParser):
schema = {
'prefixes': {
Any(): {
'size': str,
'free': str,
'type': str,
'flags': str,
}
}
}
class ShowFileSystem(FileSystemSchema):
"""Parser for show filesystem interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show filesystem'
"""
Fri Apr 16 21:22:35.610 UTC
File Systems:
Size(b) Free(b) Type Flags Prefixes
48648003584 42960728064 flash rw /misc/config
0 0 network rw tftp:
4008443904 3018457088 flash-disk rw disk2:
0 0 network rw ftp:
54744576000 53680197632 harddisk rw harddisk:
3590602752 3580395520 flash-disk rw disk0:
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
filesystem_dict = {}
result_dict = {}
"""
Variables Parsed:
size = Size
free = Free
type = Type
flags = Flags
prefixes = Prefixes
"""
p0 = re.compile(r'^(?P<size>\s*\d+)\s+(?P<free>\d+)\s+(?P<type>(\w+|\w+-\w+))\s+(?P<flags>\w+)\s+(?P<prefixes>(\w+:|.?\w+)*)')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'prefixes' not in filesystem_dict:
result_dict = filesystem_dict.setdefault('prefixes',{})
size = m.groupdict()['size']
free = m.groupdict()['free']
type_ = m.groupdict()['type']
flags = m.groupdict()['flags']
prefixes = m.groupdict()['prefixes']
result_dict[prefixes] = {}
result_dict[prefixes]['size'] = size
result_dict[prefixes]['free'] = free
result_dict[prefixes]['type'] = type_
result_dict[prefixes]['flags'] = flags
continue
return filesystem_dict
# ==========================
# Parser for 'show controllers fabric plane all'
# ==========================
# =======================================================
# Schema for `show controllers fabric plane all`
# ========================================================
class ControllersFabricPlaneAllSchema(MetaParser):
schema = {
'plane_id': {
Any(): {
'admin_state': str,
'plane_state': str,
'ud_counter': str,
'mcast_counter': str,
}
}
}
class ShowControllersFabricPlaneAll(ControllersFabricPlaneAllSchema):
"""Parser for show controller fabric plane all interface on iosxr routers
parser class - implements detail parsing mechanisms for cli output.
"""
cli_command = 'show controllers fabric plane all'
"""
Thu Jul 30 13:16:17.593 UTC
Plane Admin Plane up->dn up->mcast
Id State State counter counter
--------------------------------------
0 UP UP 0 0
1 UP UP 0 0
2 UP DN 0 0
3 UP DN 0 0
4 UP DN 0 0
5 UP DN 0 0
6 UP DN 0 0
7 UP DN 0 0
"""
def cli(self, output=None):
if output is None:
out = self.device.execute(self.cli_command)
else:
out = output
cfabric_dict = {}
result_dict = {}
"""
Variables Parsed:
plane_id = Plane ID
admin_state = Admin State
plane_state = Plane State
ud_counter = up->down counter
mcast_counter = mcast counter
"""
p0 = re.compile(r'^(?P<plane_id>\d+)\s+(?P<admin_state>\w+)\s+(?P<plane_state>\w+)\s+(?P<ud_counter>\d+)\s+(?P<mcast_counter>\d+)')
for line in out.splitlines():
line = line.strip()
m = p0.match(line)
if m:
if 'plane_id' not in cfabric_dict:
result_dict = cfabric_dict.setdefault('plane_id',{})
plane_id = m.groupdict()['plane_id']
admin_state = m.groupdict()['admin_state']
plane_state = m.groupdict()['plane_state']
ud_counter = m.groupdict()['ud_counter']
mcast_counter = m.groupdict()['mcast_counter']
result_dict[plane_id] = {}
result_dict[plane_id]['admin_state'] = admin_state
result_dict[plane_id]['plane_state'] = plane_state
result_dict[plane_id]['ud_counter'] = ud_counter
result_dict[plane_id]['mcast_counter'] = mcast_counter
continue
return cfabric_dict
| en | 0.445974 | show_media.py IOSXR parsers for the following show commands: * 'show media' * 'show filesystem' * 'show controllers fabric plane all' # ======================================================= # Schema for `show media` # ======================================================== Parser for show media interface on iosxr routers parser class - implements detail parsing mechanisms for cli output. Tue Apr 13 18:43:17.452 UTC Media info for node0_RP0_CPU0 ------------------------------------------------------------ Partition Size Used Percent Avail disk2: 3.8G 945M 25% 2.9G disk0: 3.4G 9.6M 1% 3.2G /var/lib/docker 5.6G 12M 1% 5.3G harddisk: 51G 1016M 3% 48G log: 4.5G 253M 6% 4.0G ------------------------------------------------------------ log: = system log files (read-only) Variables Parsed: partition = Partition size = Size used = Used percent = Percent avail = Avail # ========================== # Parser for 'show filesystem' # ========================== # ======================================================= # Schema for `show filesystem` # ======================================================== Parser for show filesystem interface on iosxr routers parser class - implements detail parsing mechanisms for cli output. Fri Apr 16 21:22:35.610 UTC File Systems: Size(b) Free(b) Type Flags Prefixes 48648003584 42960728064 flash rw /misc/config 0 0 network rw tftp: 4008443904 3018457088 flash-disk rw disk2: 0 0 network rw ftp: 54744576000 53680197632 harddisk rw harddisk: 3590602752 3580395520 flash-disk rw disk0: Variables Parsed: size = Size free = Free type = Type flags = Flags prefixes = Prefixes # ========================== # Parser for 'show controllers fabric plane all' # ========================== # ======================================================= # Schema for `show controllers fabric plane all` # ======================================================== Parser for show controller fabric plane all interface on iosxr routers parser class - implements detail parsing mechanisms for cli output. Thu Jul 30 13:16:17.593 UTC Plane Admin Plane up->dn up->mcast Id State State counter counter -------------------------------------- 0 UP UP 0 0 1 UP UP 0 0 2 UP DN 0 0 3 UP DN 0 0 4 UP DN 0 0 5 UP DN 0 0 6 UP DN 0 0 7 UP DN 0 0 Variables Parsed: plane_id = Plane ID admin_state = Admin State plane_state = Plane State ud_counter = up->down counter mcast_counter = mcast counter | 2.351006 | 2 |
random_or_override.py | wert23239/AzulRL | 1 | 6620635 | import random
from numpy.random import choice
"""
Returns either a random int, or an overriden value (for testing).
When overriding, pass in a sequence of ints for this function to return.
"""
class RandomOrOverride:
def __init__(self, override=[], seed=None):
self.override = override
self.override_index = 0
random.seed(seed)
def random_range(self, min, max):
if self.override_index >= len(self.override):
return random.randint(min, max)
else:
res = self.override[self.override_index]
self.override_index += 1
return res
def random_range_cont(self):
if self.override_index >= len(self.override):
return random.random()
else:
res = self.override[self.override_index]
self.override_index += 1
return res
def random_sample(self, population, k):
if self.override_index + k > len(self.override):
return random.sample(population, k)
else:
res = self.override[self.override_index:self.override_index + k]
self.override_index += k
return res
def weighted_random_choice(self, population_size, probability_distribution):
if self.override_index >= len(self.override):
return choice(population_size, p=probability_distribution)
else:
res = self.override[self.override_index]
self.override_index += 1
return res
| import random
from numpy.random import choice
"""
Returns either a random int, or an overriden value (for testing).
When overriding, pass in a sequence of ints for this function to return.
"""
class RandomOrOverride:
def __init__(self, override=[], seed=None):
self.override = override
self.override_index = 0
random.seed(seed)
def random_range(self, min, max):
if self.override_index >= len(self.override):
return random.randint(min, max)
else:
res = self.override[self.override_index]
self.override_index += 1
return res
def random_range_cont(self):
if self.override_index >= len(self.override):
return random.random()
else:
res = self.override[self.override_index]
self.override_index += 1
return res
def random_sample(self, population, k):
if self.override_index + k > len(self.override):
return random.sample(population, k)
else:
res = self.override[self.override_index:self.override_index + k]
self.override_index += k
return res
def weighted_random_choice(self, population_size, probability_distribution):
if self.override_index >= len(self.override):
return choice(population_size, p=probability_distribution)
else:
res = self.override[self.override_index]
self.override_index += 1
return res
| en | 0.786388 | Returns either a random int, or an overriden value (for testing). When overriding, pass in a sequence of ints for this function to return. | 3.829636 | 4 |
carrier/regression/mercedes-benz-greener-manufacturing/src/eda/eda.py | talk2sunil83/UpgradLearning | 0 | 6620636 | <reponame>talk2sunil83/UpgradLearning
# %% [markdown]
'''
# [Mercedes-Benz Greener Manufacturing](https://www.kaggle.com/c/mercedes-benz-greener-manufacturing) from [Kaggle](https://www.kaggle.com/)
'''
# %% [markdown]
'''
# Problem statement
Since the first automobile, the Benz Patent Motor Car in 1886, Mercedes-Benz has stood for important automotive innovations. These include, for example, the passenger safety cell with crumple zone, the airbag and intelligent assistance systems. Mercedes-Benz applies for nearly 2000 patents per year, making the brand the European leader among premium car makers. Daimler’s Mercedes-Benz cars are leaders in the premium car industry. With a huge selection of features and options, customers can choose the customized Mercedes-Benz of their dreams. .
To ensure the safety and reliability of each and every unique car configuration before they hit the road, Daimler’s engineers have developed a robust testing system. But, optimizing the speed of their testing system for so many possible feature combinations is complex and time-consuming without a powerful algorithmic approach. As one of the world’s biggest manufacturers of premium cars, safety and efficiency are paramount on Daimler’s production lines.
In this competition, **Daimler is challenging Kagglers to tackle the curse of dimensionality and reduce the time that cars spend on the test bench. Competitors will work with a dataset representing different permutations of Mercedes-Benz car features to predict the time it takes to pass testing. Winning algorithms will contribute to speedier testing, resulting in lower carbon dioxide emissions without reducing Daimler’s standards.**
'''
# %% [markdown]
'''
# Solution Approach
- Step1
- Step2
'''
# %% [markdown]
'''
**Author** : <NAME> || <EMAIL> || +91 96206 38383 ||
'''
# %% [markdown]
'''
# Solution
'''
# %% [markdown]
'''
# Lib Imports
'''
# %%
import pickle
from sklearn.decomposition import PCA
from sklearn.preprocessing import OneHotEncoder
from typing import Dict, List, Sequence, Tuple
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.figure_factory as ff
import plotly.graph_objects as go
import plotly.express as px
from IPython.display import display
from enum import Enum, auto
%matplotlib inline
# %% [markdown]
'''
# Data load
'''
# %%
base_path = '../../data/'
train = pd.read_csv(f"{base_path}train.csv.zip", compression='zip')
test = pd.read_csv(f"{base_path}test.csv.zip", compression='zip')
# %%
print(train.shape, test.shape)
# %% [markdown]
'''
# Pandas settings
'''
# %%
pd.options.display.max_columns = None
pd.options.display.max_rows = 500
pd.options.display.width = None
pd.options.display.max_colwidth = 100
pd.options.display.precision = 3
# %% [markdown]
'''
# Data Overview
'''
# %%
print(train.shape, test.shape)
# %%
train.info(verbose=1)
# %%
train.sample(10)
# %%
(train.isnull().sum()/train.shape[0])*100
# %%
train.isnull().mean()*100
# %%
# Count of data types
train.dtypes.value_counts()
# %% [markdown]
'''
# EDA
'''
# %% [markdown]
'''
# EDA Utility Functions
'''
# %%
def print_null_percents(frame: pd.DataFrame, full: bool = False, display_cols=True):
"""Prints null columns perdent and count
Args:
frame (pd.DataFrame):Dataframe where null needs to be counted
full (bool, optional): show all columns. Defaults to False.
display_cols (bool, optional): show columns or not. Defaults to True.
"""
null_counts = frame.isna().sum()
if not full:
null_counts = null_counts[null_counts > 0]
if display_cols:
display(round((null_counts/frame.shape[0])*100, 2).sort_values(ascending=False))
print(f"Columns count with null: {len(null_counts[null_counts > 0])}")
class GraphType(Enum):
"""Graph Type Enum
Args:
Enum ([type]): Built-in Enum Class
"""
BAR = auto()
LINE = auto()
DIST = auto()
def plot_univariate_series(
series: pd.Series,
title: str,
xlabel: str,
ylabel: str,
graph_type: GraphType = None,
showlegend: bool = False,
log_x=False,
log_y=False,
* args,
**kwargs) -> None:
"""Bar plots a interger series
Args:
series (pd.Series): series to be plotted
title (str): graph title
xlabel (str): x-axis label
ylabel (str): y-axis label
graph_type (GraphType, optional): graph type
showlegend (bool, optional): default False
log_x (bool, optional): default False
log_y (bool, optional): default False
"""
labels = {"x": xlabel, "y": ylabel}
fig = None
if graph_type is None or graph_type == GraphType.BAR:
fig = px.bar(x=series.index, y=series, color=series.index,
title=title, labels=labels, log_x=log_x, log_y=log_y, *args, **kwargs)
if graph_type == GraphType.LINE:
px.scatter(x=series.index, y=series, title=title, labels=labels, color=series.index, *args,
**kwargs)
fig.update_layout(showlegend=showlegend)
fig.show()
def get_univariate_cat_plot_strs(value: str, **kwargs) -> Tuple[str, str, str]:
"""Creates graph title, x-axis text and y-axis text for given value
Args:
value (str): column name
Returns:
Tuple[str, str, str]: title, x-axis text and y-axis text
"""
full_name = value # TODO: write logic to make name
if len(full_name) > 30:
full_name = value
count_str = full_name + ' Count' + " - Log Scale" if kwargs.get("log_y") else ""
return count_str + ' Plot', full_name, count_str
def plot_cat_data(c: str, value_counts_ser: pd.Series, *args, **kwargs):
"""Plots the value count series
Args:
c ([str]): column name
value_counts_ser ([pd.Series]): value counts series
"""
t, xl, yl = get_univariate_cat_plot_strs(c, **kwargs)
plot_univariate_series(value_counts_ser, t, xl, yl, *args, **kwargs)
def plot_univariate_categorical_columns(categorical_cols: Sequence[str], dataframe: pd.DataFrame, plot_limit: int = 30, print_value_counts=False, *args, **kwargs) -> None:
"""plots categorical variable bars
Args:
categorical_cols (Sequence[str]): categorical columns
dataframe (pd.DataFrame): DataFrame
"""
for c in categorical_cols:
value_counts_ser = dataframe[c].value_counts()
if print_value_counts:
print(value_counts_ser)
cnt_len = len(value_counts_ser)
if cnt_len > 1 and cnt_len < plot_limit:
plot_cat_data(c, value_counts_ser, *args, **kwargs)
def plot_dist(data_frame: pd.DataFrame, cols_to_plot: List[str], merge_all: bool = False, width=800, *args, **kwargs) -> None:
if merge_all:
fig = ff.create_distplot(hist_data=data_frame, group_labels=cols_to_plot, *args, **kwargs)
fig.update_layout(title_text=f"Dist plot for Numeric Columns", width=width)
fig.show()
else:
for _, c in enumerate(cols_to_plot):
fig = ff.create_distplot(hist_data=[data_frame[c].values], group_labels=[c], *args, **kwargs)
fig.update_layout(title_text=f"Distribution plot for {c}", width=width)
fig.show()
def plot_box(df: pd.DataFrame, x: str, y: str) -> None:
fig = px.box(df, x=x, y=y, color=x)
fig.show()
def getdtype(col_data: pd.Series):
if col_data.dtype == np.int64 or col_data.dtype == np.float64:
return 'num'
elif col_data.dtype == 'category':
return 'cat'
def plot_two_variables(df, x, y):
if getdtype(df[x]) == 'num' and getdtype(df[y]) == 'num':
fig = px.scatter(df, x=x, y=y, trendline="ols")
fig.show()
elif (getdtype(df[x]) == 'cat' and getdtype(df[y]) == 'num'):
plot_box(df, x, y)
elif (getdtype(df[x]) == 'num' and getdtype(df[y]) == 'cat'):
plot_box(df, y, x)
def set_value_count_color(value):
return "background-color: rgba(221, 207, 155, 0.1)" if value <= 5. else ''
def print_value_count_percents(categorical_cols: Sequence[str], dataframe: pd.DataFrame) -> None:
total_recs = dataframe.shape[0]
# ret_values = {}
for c in categorical_cols:
value_counts_ser = dataframe[c].value_counts()
value_counts_per = round(dataframe[c].value_counts()*100/total_recs, 2)
df = pd.DataFrame({"Value": value_counts_ser.index, "Value Counts": value_counts_ser.values, "Percent": value_counts_per.values})
df.sort_values(by="Percent", ascending=False)
# ret_values[c] = df
print(f"\nValue Counts for {c}")
# styled_df = df.style.apply(lambda row: highlight_other_group(row, col_count, 5), axis=1)
styled_df = df.style.format({
"Percent": "{:.2f}%"
}). \
applymap(set_value_count_color, subset=["Percent"]). \
hide_index()
display(styled_df)
# return ret_values
def print_count_of_uniques(dataframe: pd.DataFrame, display_res=False) -> pd.DataFrame:
cols = dataframe.columns
unique_values = []
unique_len = []
for c in cols:
uniques = dataframe[c].unique()
unique_values.append(sorted(uniques))
unique_len.append(len(uniques))
frame = pd.DataFrame({
"Column": cols,
"Unique Values": unique_values,
"Column Unique Count": unique_len})
frame.sort_values(by=["Column Unique Count", "Column"], ascending=[False, True], inplace=True)
if display_res:
display(frame.style.hide_index())
return frame
# %%
id_cols = ["ID"]
target_col = 'y'
# %% [markdown]
'''
# Univariate
'''
# %% [markdown]
'''
# value counts
'''
# %%
unique_val_frame = print_count_of_uniques(train)
single_valued_cols = sorted(list(unique_val_frame[unique_val_frame["Column Unique Count"] == 1]["Column"]))
display(unique_val_frame.style.hide_index(), single_valued_cols)
# %%
str_cols = list(train.select_dtypes('object').columns)
binary_cols = [c for c in train.columns if ((c not in single_valued_cols) and (c not in id_cols) and (c not in str_cols) and c != target_col)]
# %%
print_value_count_percents(list(str_cols), train)
# %%
print_count_of_uniques(train[binary_cols])
# %% [markdown]
'''
## Drop unwanted columns
'''
# %%
# Drop unwanted columns
cols_to_drop = id_cols + single_valued_cols
train.drop(cols_to_drop, axis=1, inplace=True)
test.drop(cols_to_drop, axis=1, inplace=True)
# %%
print(train.shape, test.shape)
# %% [markdown]
'''
# distributions
'''
# %% [markdown]
'''
# Plotting numeric and categorical
'''
# %% [markdown]
'''
## Numerics
'''
# %%
# plot target
plot_dist(train, [target_col], show_rug=False)
# %% [markdown]
'''
## categorical
'''
# %%
# Plot string valued columns frequency
plot_univariate_categorical_columns(list(str_cols), train, log_y=True, plot_limit=50)
# %%
for col in str_cols:
plot_box(train, col, 'y')
# %%
# Some binary columns
plot_univariate_categorical_columns(['X350', 'X351', 'X352', 'X353', 'X354', 'X355', 'X356', 'X357'], train, log_y=True)
# %% [markdown]
'''
# Bi-variate
'''
# %% [markdown]
'''
# Correlation
'''
# %%
train_corr = train.corr()
# %%
fig = px.imshow(train_corr)
fig.update_layout(width=1000, height=1000)
fig.show()
# %% [markdown]
'''
# Numeric-Numeric (Scatter plot)
'''
# %%
# pair plot
fig = px.scatter_matrix(train[train_corr[target_col].abs().nlargest(16).index], width=1000, height=1000)
fig.show()
# %% [markdown]
'''
# Numeric-Categorical (Box and violin)
'''
# %%
# get top 15 cols correlated with target column
top_15_cols = train_corr[target_col].abs().nlargest(16)[1:].index
for c in top_15_cols:
plot_box(train, c, 'y')
# %% [markdown]
'''
# Categorical-Categorical (Cross Table) - How to do it?
'''
# %%
# TODO: Zero-One count compare plot
# %% [markdown]
'''
# Pre processing
'''
# %% [markdown]
'''
## Pre processing Utils
'''
# %%
# def replace_values_having_less_count(dataframe: pd.DataFrame, target_cols: Sequence[str], threshold: Union[int, Sequence[int]] = 100, replace_with: Union[int, float, str, Sequence[int], Sequence[float], Sequence[str]] = "OT") -> DataFrame:
# pass
def replace_values_having_less_count(dataframe: pd.DataFrame, target_cols: Sequence[str], threshold: int = 100, replace_with="OT") -> pd.DataFrame:
for c in target_cols:
vc = dataframe[c].value_counts()
replace_dict = {v: replace_with for v in list(vc[vc <= threshold].index)}
dataframe[c] = dataframe[c].replace(replace_dict)
return dataframe
# %%
train = replace_values_having_less_count(train, train.select_dtypes('object').columns)
# %%
print_value_count_percents(list(str_cols), train)
# %%
for col in str_cols:
plot_box(train, col, 'y')
# %% [markdown]
'''
## Fix column dtypes - NA
'''
# %%
display(train.dtypes, test.dtypes)
# %% [markdown]
'''
# Null Handling - NA
'''
# %%
print(train.isna().sum().sum(),
test.isna().sum().sum())
# %% [markdown]
'''
# Scaling - NA
'''
# %% [markdown]
'''
# Conversion of categorical (OHE or mean)
'''
# %%
encoded_train = train.copy()
encoded_test = test.copy()
# Could do get_dummies but test is separate sow we need to preserver encoders
col_encoder = {}
for col in str_cols:
current_col_data = train[[col]]
ohe = OneHotEncoder(handle_unknown='ignore').fit(current_col_data)
transformed_train = ohe.transform(current_col_data).toarray()
transformed_test = ohe.transform(test[[col]]).toarray()
cols = [f"{col}_{c}" for c in ohe.categories_[0]]
encoded_train = pd.concat([encoded_train, pd.DataFrame(np.array(transformed_train), columns=cols)], axis=1)
encoded_test = pd.concat([encoded_test, pd.DataFrame(np.array(transformed_test), columns=cols)], axis=1)
encoded_train.drop(col, axis=1, inplace=True)
encoded_test.drop(col, axis=1, inplace=True)
# %%
print(train.shape, encoded_train.shape, test.shape, encoded_test.shape)
# %% [markdown]
'''
# Outlier Treatment - NA
'''
# %% [markdown]
'''
# Single valued removal - Done
'''
# %% [markdown]
'''
# ID Removal - Done
'''
# %% [markdown]
'''
# Non important column removal - NA
'''
# %% [markdown]
'''
# Feature creation - NA
'''
# %% [markdown]
'''
# Dimensionality Reduction
'''
# %%
# lets PCA with 90% information preservation
pca = PCA(0.9)
X = encoded_train.drop(target_col, axis=1)
y = encoded_train[target_col]
pca.fit(X)
encoded_train_dim_red = pca.transform(X)
encoded_test_dim_red = pca.transform(encoded_test)
# %%
def save_file(base_path, object, filename) -> None:
with open(f"{base_path}{filename}.pkl", 'wb') as f:
f.write(pickle.dumps(object))
save_file(base_path, encoded_train, 'encoded_train')
save_file(base_path, encoded_test, 'encoded_test')
save_file(base_path, encoded_train_dim_red, 'encoded_train_dim_red')
save_file(base_path, encoded_test_dim_red, 'encoded_test_dim_red')
# encoded_train.to_pickle(f"{base_path}encoded_train.pkl")
# encoded_test.to_pickle(f"{base_path}encoded_test.pkl")
# encoded_train_dim_red.to_pickle(f"{base_path}encoded_train_dim_red.pkl")
# encoded_test_dim_red.to_pickle(f"{base_path}encoded_test_dim_red.pkl")
# %%
# %%
# %%
# %%
| # %% [markdown]
'''
# [Mercedes-Benz Greener Manufacturing](https://www.kaggle.com/c/mercedes-benz-greener-manufacturing) from [Kaggle](https://www.kaggle.com/)
'''
# %% [markdown]
'''
# Problem statement
Since the first automobile, the Benz Patent Motor Car in 1886, Mercedes-Benz has stood for important automotive innovations. These include, for example, the passenger safety cell with crumple zone, the airbag and intelligent assistance systems. Mercedes-Benz applies for nearly 2000 patents per year, making the brand the European leader among premium car makers. Daimler’s Mercedes-Benz cars are leaders in the premium car industry. With a huge selection of features and options, customers can choose the customized Mercedes-Benz of their dreams. .
To ensure the safety and reliability of each and every unique car configuration before they hit the road, Daimler’s engineers have developed a robust testing system. But, optimizing the speed of their testing system for so many possible feature combinations is complex and time-consuming without a powerful algorithmic approach. As one of the world’s biggest manufacturers of premium cars, safety and efficiency are paramount on Daimler’s production lines.
In this competition, **Daimler is challenging Kagglers to tackle the curse of dimensionality and reduce the time that cars spend on the test bench. Competitors will work with a dataset representing different permutations of Mercedes-Benz car features to predict the time it takes to pass testing. Winning algorithms will contribute to speedier testing, resulting in lower carbon dioxide emissions without reducing Daimler’s standards.**
'''
# %% [markdown]
'''
# Solution Approach
- Step1
- Step2
'''
# %% [markdown]
'''
**Author** : <NAME> || <EMAIL> || +91 96206 38383 ||
'''
# %% [markdown]
'''
# Solution
'''
# %% [markdown]
'''
# Lib Imports
'''
# %%
import pickle
from sklearn.decomposition import PCA
from sklearn.preprocessing import OneHotEncoder
from typing import Dict, List, Sequence, Tuple
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.figure_factory as ff
import plotly.graph_objects as go
import plotly.express as px
from IPython.display import display
from enum import Enum, auto
%matplotlib inline
# %% [markdown]
'''
# Data load
'''
# %%
base_path = '../../data/'
train = pd.read_csv(f"{base_path}train.csv.zip", compression='zip')
test = pd.read_csv(f"{base_path}test.csv.zip", compression='zip')
# %%
print(train.shape, test.shape)
# %% [markdown]
'''
# Pandas settings
'''
# %%
pd.options.display.max_columns = None
pd.options.display.max_rows = 500
pd.options.display.width = None
pd.options.display.max_colwidth = 100
pd.options.display.precision = 3
# %% [markdown]
'''
# Data Overview
'''
# %%
print(train.shape, test.shape)
# %%
train.info(verbose=1)
# %%
train.sample(10)
# %%
(train.isnull().sum()/train.shape[0])*100
# %%
train.isnull().mean()*100
# %%
# Count of data types
train.dtypes.value_counts()
# %% [markdown]
'''
# EDA
'''
# %% [markdown]
'''
# EDA Utility Functions
'''
# %%
def print_null_percents(frame: pd.DataFrame, full: bool = False, display_cols=True):
"""Prints null columns perdent and count
Args:
frame (pd.DataFrame):Dataframe where null needs to be counted
full (bool, optional): show all columns. Defaults to False.
display_cols (bool, optional): show columns or not. Defaults to True.
"""
null_counts = frame.isna().sum()
if not full:
null_counts = null_counts[null_counts > 0]
if display_cols:
display(round((null_counts/frame.shape[0])*100, 2).sort_values(ascending=False))
print(f"Columns count with null: {len(null_counts[null_counts > 0])}")
class GraphType(Enum):
"""Graph Type Enum
Args:
Enum ([type]): Built-in Enum Class
"""
BAR = auto()
LINE = auto()
DIST = auto()
def plot_univariate_series(
series: pd.Series,
title: str,
xlabel: str,
ylabel: str,
graph_type: GraphType = None,
showlegend: bool = False,
log_x=False,
log_y=False,
* args,
**kwargs) -> None:
"""Bar plots a interger series
Args:
series (pd.Series): series to be plotted
title (str): graph title
xlabel (str): x-axis label
ylabel (str): y-axis label
graph_type (GraphType, optional): graph type
showlegend (bool, optional): default False
log_x (bool, optional): default False
log_y (bool, optional): default False
"""
labels = {"x": xlabel, "y": ylabel}
fig = None
if graph_type is None or graph_type == GraphType.BAR:
fig = px.bar(x=series.index, y=series, color=series.index,
title=title, labels=labels, log_x=log_x, log_y=log_y, *args, **kwargs)
if graph_type == GraphType.LINE:
px.scatter(x=series.index, y=series, title=title, labels=labels, color=series.index, *args,
**kwargs)
fig.update_layout(showlegend=showlegend)
fig.show()
def get_univariate_cat_plot_strs(value: str, **kwargs) -> Tuple[str, str, str]:
"""Creates graph title, x-axis text and y-axis text for given value
Args:
value (str): column name
Returns:
Tuple[str, str, str]: title, x-axis text and y-axis text
"""
full_name = value # TODO: write logic to make name
if len(full_name) > 30:
full_name = value
count_str = full_name + ' Count' + " - Log Scale" if kwargs.get("log_y") else ""
return count_str + ' Plot', full_name, count_str
def plot_cat_data(c: str, value_counts_ser: pd.Series, *args, **kwargs):
"""Plots the value count series
Args:
c ([str]): column name
value_counts_ser ([pd.Series]): value counts series
"""
t, xl, yl = get_univariate_cat_plot_strs(c, **kwargs)
plot_univariate_series(value_counts_ser, t, xl, yl, *args, **kwargs)
def plot_univariate_categorical_columns(categorical_cols: Sequence[str], dataframe: pd.DataFrame, plot_limit: int = 30, print_value_counts=False, *args, **kwargs) -> None:
"""plots categorical variable bars
Args:
categorical_cols (Sequence[str]): categorical columns
dataframe (pd.DataFrame): DataFrame
"""
for c in categorical_cols:
value_counts_ser = dataframe[c].value_counts()
if print_value_counts:
print(value_counts_ser)
cnt_len = len(value_counts_ser)
if cnt_len > 1 and cnt_len < plot_limit:
plot_cat_data(c, value_counts_ser, *args, **kwargs)
def plot_dist(data_frame: pd.DataFrame, cols_to_plot: List[str], merge_all: bool = False, width=800, *args, **kwargs) -> None:
if merge_all:
fig = ff.create_distplot(hist_data=data_frame, group_labels=cols_to_plot, *args, **kwargs)
fig.update_layout(title_text=f"Dist plot for Numeric Columns", width=width)
fig.show()
else:
for _, c in enumerate(cols_to_plot):
fig = ff.create_distplot(hist_data=[data_frame[c].values], group_labels=[c], *args, **kwargs)
fig.update_layout(title_text=f"Distribution plot for {c}", width=width)
fig.show()
def plot_box(df: pd.DataFrame, x: str, y: str) -> None:
fig = px.box(df, x=x, y=y, color=x)
fig.show()
def getdtype(col_data: pd.Series):
if col_data.dtype == np.int64 or col_data.dtype == np.float64:
return 'num'
elif col_data.dtype == 'category':
return 'cat'
def plot_two_variables(df, x, y):
if getdtype(df[x]) == 'num' and getdtype(df[y]) == 'num':
fig = px.scatter(df, x=x, y=y, trendline="ols")
fig.show()
elif (getdtype(df[x]) == 'cat' and getdtype(df[y]) == 'num'):
plot_box(df, x, y)
elif (getdtype(df[x]) == 'num' and getdtype(df[y]) == 'cat'):
plot_box(df, y, x)
def set_value_count_color(value):
return "background-color: rgba(221, 207, 155, 0.1)" if value <= 5. else ''
def print_value_count_percents(categorical_cols: Sequence[str], dataframe: pd.DataFrame) -> None:
total_recs = dataframe.shape[0]
# ret_values = {}
for c in categorical_cols:
value_counts_ser = dataframe[c].value_counts()
value_counts_per = round(dataframe[c].value_counts()*100/total_recs, 2)
df = pd.DataFrame({"Value": value_counts_ser.index, "Value Counts": value_counts_ser.values, "Percent": value_counts_per.values})
df.sort_values(by="Percent", ascending=False)
# ret_values[c] = df
print(f"\nValue Counts for {c}")
# styled_df = df.style.apply(lambda row: highlight_other_group(row, col_count, 5), axis=1)
styled_df = df.style.format({
"Percent": "{:.2f}%"
}). \
applymap(set_value_count_color, subset=["Percent"]). \
hide_index()
display(styled_df)
# return ret_values
def print_count_of_uniques(dataframe: pd.DataFrame, display_res=False) -> pd.DataFrame:
cols = dataframe.columns
unique_values = []
unique_len = []
for c in cols:
uniques = dataframe[c].unique()
unique_values.append(sorted(uniques))
unique_len.append(len(uniques))
frame = pd.DataFrame({
"Column": cols,
"Unique Values": unique_values,
"Column Unique Count": unique_len})
frame.sort_values(by=["Column Unique Count", "Column"], ascending=[False, True], inplace=True)
if display_res:
display(frame.style.hide_index())
return frame
# %%
id_cols = ["ID"]
target_col = 'y'
# %% [markdown]
'''
# Univariate
'''
# %% [markdown]
'''
# value counts
'''
# %%
unique_val_frame = print_count_of_uniques(train)
single_valued_cols = sorted(list(unique_val_frame[unique_val_frame["Column Unique Count"] == 1]["Column"]))
display(unique_val_frame.style.hide_index(), single_valued_cols)
# %%
str_cols = list(train.select_dtypes('object').columns)
binary_cols = [c for c in train.columns if ((c not in single_valued_cols) and (c not in id_cols) and (c not in str_cols) and c != target_col)]
# %%
print_value_count_percents(list(str_cols), train)
# %%
print_count_of_uniques(train[binary_cols])
# %% [markdown]
'''
## Drop unwanted columns
'''
# %%
# Drop unwanted columns
cols_to_drop = id_cols + single_valued_cols
train.drop(cols_to_drop, axis=1, inplace=True)
test.drop(cols_to_drop, axis=1, inplace=True)
# %%
print(train.shape, test.shape)
# %% [markdown]
'''
# distributions
'''
# %% [markdown]
'''
# Plotting numeric and categorical
'''
# %% [markdown]
'''
## Numerics
'''
# %%
# plot target
plot_dist(train, [target_col], show_rug=False)
# %% [markdown]
'''
## categorical
'''
# %%
# Plot string valued columns frequency
plot_univariate_categorical_columns(list(str_cols), train, log_y=True, plot_limit=50)
# %%
for col in str_cols:
plot_box(train, col, 'y')
# %%
# Some binary columns
plot_univariate_categorical_columns(['X350', 'X351', 'X352', 'X353', 'X354', 'X355', 'X356', 'X357'], train, log_y=True)
# %% [markdown]
'''
# Bi-variate
'''
# %% [markdown]
'''
# Correlation
'''
# %%
train_corr = train.corr()
# %%
fig = px.imshow(train_corr)
fig.update_layout(width=1000, height=1000)
fig.show()
# %% [markdown]
'''
# Numeric-Numeric (Scatter plot)
'''
# %%
# pair plot
fig = px.scatter_matrix(train[train_corr[target_col].abs().nlargest(16).index], width=1000, height=1000)
fig.show()
# %% [markdown]
'''
# Numeric-Categorical (Box and violin)
'''
# %%
# get top 15 cols correlated with target column
top_15_cols = train_corr[target_col].abs().nlargest(16)[1:].index
for c in top_15_cols:
plot_box(train, c, 'y')
# %% [markdown]
'''
# Categorical-Categorical (Cross Table) - How to do it?
'''
# %%
# TODO: Zero-One count compare plot
# %% [markdown]
'''
# Pre processing
'''
# %% [markdown]
'''
## Pre processing Utils
'''
# %%
# def replace_values_having_less_count(dataframe: pd.DataFrame, target_cols: Sequence[str], threshold: Union[int, Sequence[int]] = 100, replace_with: Union[int, float, str, Sequence[int], Sequence[float], Sequence[str]] = "OT") -> DataFrame:
# pass
def replace_values_having_less_count(dataframe: pd.DataFrame, target_cols: Sequence[str], threshold: int = 100, replace_with="OT") -> pd.DataFrame:
for c in target_cols:
vc = dataframe[c].value_counts()
replace_dict = {v: replace_with for v in list(vc[vc <= threshold].index)}
dataframe[c] = dataframe[c].replace(replace_dict)
return dataframe
# %%
train = replace_values_having_less_count(train, train.select_dtypes('object').columns)
# %%
print_value_count_percents(list(str_cols), train)
# %%
for col in str_cols:
plot_box(train, col, 'y')
# %% [markdown]
'''
## Fix column dtypes - NA
'''
# %%
display(train.dtypes, test.dtypes)
# %% [markdown]
'''
# Null Handling - NA
'''
# %%
print(train.isna().sum().sum(),
test.isna().sum().sum())
# %% [markdown]
'''
# Scaling - NA
'''
# %% [markdown]
'''
# Conversion of categorical (OHE or mean)
'''
# %%
encoded_train = train.copy()
encoded_test = test.copy()
# Could do get_dummies but test is separate sow we need to preserver encoders
col_encoder = {}
for col in str_cols:
current_col_data = train[[col]]
ohe = OneHotEncoder(handle_unknown='ignore').fit(current_col_data)
transformed_train = ohe.transform(current_col_data).toarray()
transformed_test = ohe.transform(test[[col]]).toarray()
cols = [f"{col}_{c}" for c in ohe.categories_[0]]
encoded_train = pd.concat([encoded_train, pd.DataFrame(np.array(transformed_train), columns=cols)], axis=1)
encoded_test = pd.concat([encoded_test, pd.DataFrame(np.array(transformed_test), columns=cols)], axis=1)
encoded_train.drop(col, axis=1, inplace=True)
encoded_test.drop(col, axis=1, inplace=True)
# %%
print(train.shape, encoded_train.shape, test.shape, encoded_test.shape)
# %% [markdown]
'''
# Outlier Treatment - NA
'''
# %% [markdown]
'''
# Single valued removal - Done
'''
# %% [markdown]
'''
# ID Removal - Done
'''
# %% [markdown]
'''
# Non important column removal - NA
'''
# %% [markdown]
'''
# Feature creation - NA
'''
# %% [markdown]
'''
# Dimensionality Reduction
'''
# %%
# lets PCA with 90% information preservation
pca = PCA(0.9)
X = encoded_train.drop(target_col, axis=1)
y = encoded_train[target_col]
pca.fit(X)
encoded_train_dim_red = pca.transform(X)
encoded_test_dim_red = pca.transform(encoded_test)
# %%
def save_file(base_path, object, filename) -> None:
with open(f"{base_path}{filename}.pkl", 'wb') as f:
f.write(pickle.dumps(object))
save_file(base_path, encoded_train, 'encoded_train')
save_file(base_path, encoded_test, 'encoded_test')
save_file(base_path, encoded_train_dim_red, 'encoded_train_dim_red')
save_file(base_path, encoded_test_dim_red, 'encoded_test_dim_red')
# encoded_train.to_pickle(f"{base_path}encoded_train.pkl")
# encoded_test.to_pickle(f"{base_path}encoded_test.pkl")
# encoded_train_dim_red.to_pickle(f"{base_path}encoded_train_dim_red.pkl")
# encoded_test_dim_red.to_pickle(f"{base_path}encoded_test_dim_red.pkl")
# %%
# %%
# %%
# %% | en | 0.627694 | # %% [markdown] # [Mercedes-Benz Greener Manufacturing](https://www.kaggle.com/c/mercedes-benz-greener-manufacturing) from [Kaggle](https://www.kaggle.com/) # %% [markdown] # Problem statement
Since the first automobile, the Benz Patent Motor Car in 1886, Mercedes-Benz has stood for important automotive innovations. These include, for example, the passenger safety cell with crumple zone, the airbag and intelligent assistance systems. Mercedes-Benz applies for nearly 2000 patents per year, making the brand the European leader among premium car makers. Daimler’s Mercedes-Benz cars are leaders in the premium car industry. With a huge selection of features and options, customers can choose the customized Mercedes-Benz of their dreams. .
To ensure the safety and reliability of each and every unique car configuration before they hit the road, Daimler’s engineers have developed a robust testing system. But, optimizing the speed of their testing system for so many possible feature combinations is complex and time-consuming without a powerful algorithmic approach. As one of the world’s biggest manufacturers of premium cars, safety and efficiency are paramount on Daimler’s production lines.
In this competition, **Daimler is challenging Kagglers to tackle the curse of dimensionality and reduce the time that cars spend on the test bench. Competitors will work with a dataset representing different permutations of Mercedes-Benz car features to predict the time it takes to pass testing. Winning algorithms will contribute to speedier testing, resulting in lower carbon dioxide emissions without reducing Daimler’s standards.** # %% [markdown] # Solution Approach
- Step1
- Step2 # %% [markdown] **Author** : <NAME> || <EMAIL> || +91 96206 38383 || # %% [markdown] # Solution # %% [markdown] # Lib Imports # %% # %% [markdown] # Data load # %% # %% # %% [markdown] # Pandas settings # %% # %% [markdown] # Data Overview # %% # %% # %% # %% # %% # %% # Count of data types # %% [markdown] # EDA # %% [markdown] # EDA Utility Functions # %% Prints null columns perdent and count
Args:
frame (pd.DataFrame):Dataframe where null needs to be counted
full (bool, optional): show all columns. Defaults to False.
display_cols (bool, optional): show columns or not. Defaults to True. Graph Type Enum
Args:
Enum ([type]): Built-in Enum Class Bar plots a interger series
Args:
series (pd.Series): series to be plotted
title (str): graph title
xlabel (str): x-axis label
ylabel (str): y-axis label
graph_type (GraphType, optional): graph type
showlegend (bool, optional): default False
log_x (bool, optional): default False
log_y (bool, optional): default False Creates graph title, x-axis text and y-axis text for given value
Args:
value (str): column name
Returns:
Tuple[str, str, str]: title, x-axis text and y-axis text # TODO: write logic to make name Plots the value count series
Args:
c ([str]): column name
value_counts_ser ([pd.Series]): value counts series plots categorical variable bars
Args:
categorical_cols (Sequence[str]): categorical columns
dataframe (pd.DataFrame): DataFrame # ret_values = {} # ret_values[c] = df # styled_df = df.style.apply(lambda row: highlight_other_group(row, col_count, 5), axis=1) # return ret_values # %% # %% [markdown] # Univariate # %% [markdown] # value counts # %% # %% # %% # %% # %% [markdown] ## Drop unwanted columns # %% # Drop unwanted columns # %% # %% [markdown] # distributions # %% [markdown] # Plotting numeric and categorical # %% [markdown] ## Numerics # %% # plot target # %% [markdown] ## categorical # %% # Plot string valued columns frequency # %% # %% # Some binary columns # %% [markdown] # Bi-variate # %% [markdown] # Correlation # %% # %% # %% [markdown] # Numeric-Numeric (Scatter plot) # %% # pair plot # %% [markdown] # Numeric-Categorical (Box and violin) # %% # get top 15 cols correlated with target column # %% [markdown] # Categorical-Categorical (Cross Table) - How to do it? # %% # TODO: Zero-One count compare plot # %% [markdown] # Pre processing # %% [markdown] ## Pre processing Utils # %% # def replace_values_having_less_count(dataframe: pd.DataFrame, target_cols: Sequence[str], threshold: Union[int, Sequence[int]] = 100, replace_with: Union[int, float, str, Sequence[int], Sequence[float], Sequence[str]] = "OT") -> DataFrame: # pass # %% # %% # %% # %% [markdown] ## Fix column dtypes - NA # %% # %% [markdown] # Null Handling - NA # %% # %% [markdown] # Scaling - NA # %% [markdown] # Conversion of categorical (OHE or mean) # %% # Could do get_dummies but test is separate sow we need to preserver encoders # %% # %% [markdown] # Outlier Treatment - NA # %% [markdown] # Single valued removal - Done # %% [markdown] # ID Removal - Done # %% [markdown] # Non important column removal - NA # %% [markdown] # Feature creation - NA # %% [markdown] # Dimensionality Reduction # %% # lets PCA with 90% information preservation # %% # encoded_train.to_pickle(f"{base_path}encoded_train.pkl") # encoded_test.to_pickle(f"{base_path}encoded_test.pkl") # encoded_train_dim_red.to_pickle(f"{base_path}encoded_train_dim_red.pkl") # encoded_test_dim_red.to_pickle(f"{base_path}encoded_test_dim_red.pkl") # %% # %% # %% # %% | 2.69909 | 3 |
test/common.py | xharaken/john-law-coin | 75 | 6620637 | #!/usr/bin/env python3
#
# Copyright (c) 2021 <NAME>
#
# This software is released under the MIT License.
# http://opensource.org/licenses/mit-license.php
import glob, os, subprocess, sys, time
def kill_ganache():
kill_command = [
"ps axf | grep ganache | grep -v grep |" +
"awk '{ print $1 }' | xargs kill -9"]
kill_proc = subprocess.Popen(
kill_command, shell=True, stdin=subprocess.DEVNULL,
stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
kill_proc.communicate()
# Remove tmp files generated by Truffle.
command = "rm -rf /tmp/tmp-*/* 2> /dev/null"
subprocess.run(command, shell=True)
command = "rm -rf /tmp/tmp-* 2> /dev/null"
subprocess.run(command, shell=True)
for file in glob.glob("/tmp/tmp-*/*"):
command = "rm -rf " + file + " 2> /dev/null"
subprocess.run(command, shell=True)
for file in glob.glob("/tmp/tmp-*"):
command = "rm -rf " + file + " 2> /dev/null"
subprocess.run(command, shell=True)
def reset_network(voters):
# os.chdir(os.path.dirname(os.path.abspath(__file__)))
kill_ganache()
time.sleep(6)
network = subprocess.Popen(
"ganache-cli --port 8546 -l 1200000000 -a" + str(voters), shell=True,
stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
time.sleep(6)
def run_test(command):
print(command, file=sys.stderr)
subprocess.run(command, shell=True)
sys.stdout.flush()
kill_ganache()
| #!/usr/bin/env python3
#
# Copyright (c) 2021 <NAME>
#
# This software is released under the MIT License.
# http://opensource.org/licenses/mit-license.php
import glob, os, subprocess, sys, time
def kill_ganache():
kill_command = [
"ps axf | grep ganache | grep -v grep |" +
"awk '{ print $1 }' | xargs kill -9"]
kill_proc = subprocess.Popen(
kill_command, shell=True, stdin=subprocess.DEVNULL,
stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
kill_proc.communicate()
# Remove tmp files generated by Truffle.
command = "rm -rf /tmp/tmp-*/* 2> /dev/null"
subprocess.run(command, shell=True)
command = "rm -rf /tmp/tmp-* 2> /dev/null"
subprocess.run(command, shell=True)
for file in glob.glob("/tmp/tmp-*/*"):
command = "rm -rf " + file + " 2> /dev/null"
subprocess.run(command, shell=True)
for file in glob.glob("/tmp/tmp-*"):
command = "rm -rf " + file + " 2> /dev/null"
subprocess.run(command, shell=True)
def reset_network(voters):
# os.chdir(os.path.dirname(os.path.abspath(__file__)))
kill_ganache()
time.sleep(6)
network = subprocess.Popen(
"ganache-cli --port 8546 -l 1200000000 -a" + str(voters), shell=True,
stdin=subprocess.DEVNULL, stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
time.sleep(6)
def run_test(command):
print(command, file=sys.stderr)
subprocess.run(command, shell=True)
sys.stdout.flush()
kill_ganache()
| en | 0.536406 | #!/usr/bin/env python3 # # Copyright (c) 2021 <NAME> # # This software is released under the MIT License. # http://opensource.org/licenses/mit-license.php # Remove tmp files generated by Truffle. # os.chdir(os.path.dirname(os.path.abspath(__file__))) | 2.073221 | 2 |
python/spacy_lemmatizer/lemmatizer_app.py | bakdata/common-kafka-streams-demo | 4 | 6620638 | from typing import Dict, Union, List
from faust import TopicT
from faust.serializers.codecs import codecs
from faust_bootstrap.core.app import FaustApplication
from faust_bootstrap.core.streams.models import DeadLetter
from faust_s3_backed_serializer import S3BackedSerializer
from spacy_lemmatizer.lemmatizer.agent import create_spacy_agent
from spacy_lemmatizer.models import Text, LemmaText
class LemmatizerApp(FaustApplication):
s3_serde: bool
input_topics: TopicT
output_topic: TopicT
error_topic: TopicT
def __init__(self):
super(LemmatizerApp, self).__init__()
def _register_parameters(self):
self.register_parameter("--s3-serde", False, "Activate s3-backed SerDe as serializer", bool, default=False)
def get_unique_app_id(self):
return f'spacy-lemmatizer-{self.output_topic_name}'
def get_serde_avro_from_topic(self, topic: Union[str, List[str]]):
value = self.create_avro_serde(topic, False)
return value
def create_s3_serde(self, topic: Union[str, List[str]]):
value_s3_serializer = self.create_s3_backed_serde(topic, self._generate_streams_config())
value_avro = self.get_serde_avro_from_topic(topic)
return value_avro | value_s3_serializer
def create_serde(self, topic: Union[str, List[str]]):
if self.s3_serde:
return self.create_s3_serde(topic)
else:
return self.get_serde_avro_from_topic(topic)
def setup_topics(self):
value_serializer_input = self.create_serde(self.input_topic_names[0])
value_serializer_output = self.create_serde(self.output_topic_name)
schema_input = self.create_schema_from(codecs["raw"], value_serializer_input, bytes, Text)
schema_output = self.create_schema_from(codecs["raw"], value_serializer_output, bytes, LemmaText)
value_serializer_error = self.create_avro_serde(self.error_topic_name, False)
schema_error = self.create_schema_from(codecs["raw"], value_serializer_error, bytes, DeadLetter)
self.input_topics = self.get_topic_from_schema(self.input_topic_names, schema_input)
self.output_topic = self.get_topic_from_schema(self.output_topic_name, schema_output)
if self.error_topic_name:
self.error_topic = self.get_topic_from_schema(self.error_topic_name, schema_error)
def build_topology(self):
agent = create_spacy_agent(self.output_topic, self.error_topic)
self.create_agent(agent, self.input_topics)
@staticmethod
def create_s3_backed_serde(topic: str, s3_config: Dict[str, str], is_key: bool = False):
base_path = s3_config.get("s3backed.base.path")
max_size = int(s3_config.get("s3backed.max.byte.size"))
region_name = s3_config.get("s3backed.region")
faust_s3_serializer = S3BackedSerializer(topic, base_path, region_name, None, max_size,
is_key)
return faust_s3_serializer
| from typing import Dict, Union, List
from faust import TopicT
from faust.serializers.codecs import codecs
from faust_bootstrap.core.app import FaustApplication
from faust_bootstrap.core.streams.models import DeadLetter
from faust_s3_backed_serializer import S3BackedSerializer
from spacy_lemmatizer.lemmatizer.agent import create_spacy_agent
from spacy_lemmatizer.models import Text, LemmaText
class LemmatizerApp(FaustApplication):
s3_serde: bool
input_topics: TopicT
output_topic: TopicT
error_topic: TopicT
def __init__(self):
super(LemmatizerApp, self).__init__()
def _register_parameters(self):
self.register_parameter("--s3-serde", False, "Activate s3-backed SerDe as serializer", bool, default=False)
def get_unique_app_id(self):
return f'spacy-lemmatizer-{self.output_topic_name}'
def get_serde_avro_from_topic(self, topic: Union[str, List[str]]):
value = self.create_avro_serde(topic, False)
return value
def create_s3_serde(self, topic: Union[str, List[str]]):
value_s3_serializer = self.create_s3_backed_serde(topic, self._generate_streams_config())
value_avro = self.get_serde_avro_from_topic(topic)
return value_avro | value_s3_serializer
def create_serde(self, topic: Union[str, List[str]]):
if self.s3_serde:
return self.create_s3_serde(topic)
else:
return self.get_serde_avro_from_topic(topic)
def setup_topics(self):
value_serializer_input = self.create_serde(self.input_topic_names[0])
value_serializer_output = self.create_serde(self.output_topic_name)
schema_input = self.create_schema_from(codecs["raw"], value_serializer_input, bytes, Text)
schema_output = self.create_schema_from(codecs["raw"], value_serializer_output, bytes, LemmaText)
value_serializer_error = self.create_avro_serde(self.error_topic_name, False)
schema_error = self.create_schema_from(codecs["raw"], value_serializer_error, bytes, DeadLetter)
self.input_topics = self.get_topic_from_schema(self.input_topic_names, schema_input)
self.output_topic = self.get_topic_from_schema(self.output_topic_name, schema_output)
if self.error_topic_name:
self.error_topic = self.get_topic_from_schema(self.error_topic_name, schema_error)
def build_topology(self):
agent = create_spacy_agent(self.output_topic, self.error_topic)
self.create_agent(agent, self.input_topics)
@staticmethod
def create_s3_backed_serde(topic: str, s3_config: Dict[str, str], is_key: bool = False):
base_path = s3_config.get("s3backed.base.path")
max_size = int(s3_config.get("s3backed.max.byte.size"))
region_name = s3_config.get("s3backed.region")
faust_s3_serializer = S3BackedSerializer(topic, base_path, region_name, None, max_size,
is_key)
return faust_s3_serializer
| none | 1 | 2.036945 | 2 | |
2-control-flow/sals-shipping/shipping.py | Dianicata/learn-python | 0 | 6620639 | <gh_stars>0
# Sal's Shipping
# Dianicata
currency ="$"
import random
weight = random.randint(1, 150)
print("current random weight: " + str(weight))
# weight = 1.5
#Ground shipping
ground_shipping_flat_charge = 20
if weight <= 2 and weight >= 0:
ground_shipment_cost = round(weight * 1.50 + ground_shipping_flat_charge, 2)
elif weight >= 2 and weight <= 6:
ground_shipment_cost = round(weight * 3 + ground_shipping_flat_charge, 2)
elif weight >= 6 and weight <=10:
ground_shipment_cost = round(weight * 4 + ground_shipping_flat_charge, 2)
elif weight > 10:
ground_shipment_cost = round(weight * 4.75 + ground_shipping_flat_charge, 2)
else:
ground_shipment_cost = "Error: Please tell me the right weight of your package"
print(f"Ground shipping option: {ground_shipment_cost}" + currency)
# Ground_shipping_premium
premium_flat_charge = 125
print(f"Premium flat charge: {premium_flat_charge}" + currency)
# drone shipping
if weight <= 2 and weight >= 0:
drone_shipment_cost = round(weight * 4.50, 2)
elif weight >= 2 and weight <= 6:
drone_shipment_cost = round(weight * 9, 2)
elif weight >= 6 and weight <= 10:
drone_shipment_cost = round(weight * 12, 2)
elif weight > 10:
drone_shipment_cost = round(weight * 14.25, 2)
else:
drone_shipment_cost = "Error: Please tell me the right weight of your package"
print(f"Drone shipping option: {drone_shipment_cost}" + currency)
# Cheapest option
shipping_option = ""
shipping_cost = 0
if ground_shipment_cost < premium_flat_charge and ground_shipment_cost < drone_shipment_cost:
shipping_option = "ground shipping"
shipping_cost = ground_shipment_cost
elif premium_flat_charge < ground_shipment_cost and premium_flat_charge < drone_shipment_cost:
shipping_option = "premium flat charge"
shipping_cost = premium_flat_charge
elif drone_shipment_cost < premium_flat_charge and drone_shipment_cost < ground_shipment_cost:
shipping_option = "drone shipping"
shipping_cost = drone_shipment_cost
print(f"Cheapest shipment option is with {shipping_option}: {shipping_cost}" + currency) | # Sal's Shipping
# Dianicata
currency ="$"
import random
weight = random.randint(1, 150)
print("current random weight: " + str(weight))
# weight = 1.5
#Ground shipping
ground_shipping_flat_charge = 20
if weight <= 2 and weight >= 0:
ground_shipment_cost = round(weight * 1.50 + ground_shipping_flat_charge, 2)
elif weight >= 2 and weight <= 6:
ground_shipment_cost = round(weight * 3 + ground_shipping_flat_charge, 2)
elif weight >= 6 and weight <=10:
ground_shipment_cost = round(weight * 4 + ground_shipping_flat_charge, 2)
elif weight > 10:
ground_shipment_cost = round(weight * 4.75 + ground_shipping_flat_charge, 2)
else:
ground_shipment_cost = "Error: Please tell me the right weight of your package"
print(f"Ground shipping option: {ground_shipment_cost}" + currency)
# Ground_shipping_premium
premium_flat_charge = 125
print(f"Premium flat charge: {premium_flat_charge}" + currency)
# drone shipping
if weight <= 2 and weight >= 0:
drone_shipment_cost = round(weight * 4.50, 2)
elif weight >= 2 and weight <= 6:
drone_shipment_cost = round(weight * 9, 2)
elif weight >= 6 and weight <= 10:
drone_shipment_cost = round(weight * 12, 2)
elif weight > 10:
drone_shipment_cost = round(weight * 14.25, 2)
else:
drone_shipment_cost = "Error: Please tell me the right weight of your package"
print(f"Drone shipping option: {drone_shipment_cost}" + currency)
# Cheapest option
shipping_option = ""
shipping_cost = 0
if ground_shipment_cost < premium_flat_charge and ground_shipment_cost < drone_shipment_cost:
shipping_option = "ground shipping"
shipping_cost = ground_shipment_cost
elif premium_flat_charge < ground_shipment_cost and premium_flat_charge < drone_shipment_cost:
shipping_option = "premium flat charge"
shipping_cost = premium_flat_charge
elif drone_shipment_cost < premium_flat_charge and drone_shipment_cost < ground_shipment_cost:
shipping_option = "drone shipping"
shipping_cost = drone_shipment_cost
print(f"Cheapest shipment option is with {shipping_option}: {shipping_cost}" + currency) | en | 0.831579 | # Sal's Shipping # Dianicata # weight = 1.5 #Ground shipping # Ground_shipping_premium # drone shipping # Cheapest option | 3.65684 | 4 |
dev/Gems/CloudGemMetric/v1/AWS/common-code/MemoryUtils/mem_util.py | BadDevCode/lumberyard | 1,738 | 6620640 | <gh_stars>1000+
#
# All or portions of this file Copyright (c) Amazon.com, Inc. or its affiliates or
# its licensors.
#
# For complete copyright and license terms please see the LICENSE at the root of this
# distribution (the "License"). All use of this software is governed by the License,
# or, if provided, by the license below or the license accompanying this file. Do not
# remove or modify any license notices. This file is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#
import time
import metric_constant as c
import os
import psutil
def get_memory_usage():
memory = psutil.virtual_memory()
return memory.percent
def get_process_memory_usage_bytes():
pid = os.getpid()
py = psutil.Process(pid)
memoryUseBytes = py.memory_info()[0]/2
return memoryUseBytes
def get_process_memory_usage_kilobytes():
return get_process_memory_usage_bytes()/1024
def get_process_memory_usage_megabytes():
return get_process_memory_usage_kilobytes()/1024
def get_memory_object():
return psutil.virtual_memory() | #
# All or portions of this file Copyright (c) Amazon.com, Inc. or its affiliates or
# its licensors.
#
# For complete copyright and license terms please see the LICENSE at the root of this
# distribution (the "License"). All use of this software is governed by the License,
# or, if provided, by the license below or the license accompanying this file. Do not
# remove or modify any license notices. This file is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#
import time
import metric_constant as c
import os
import psutil
def get_memory_usage():
memory = psutil.virtual_memory()
return memory.percent
def get_process_memory_usage_bytes():
pid = os.getpid()
py = psutil.Process(pid)
memoryUseBytes = py.memory_info()[0]/2
return memoryUseBytes
def get_process_memory_usage_kilobytes():
return get_process_memory_usage_bytes()/1024
def get_process_memory_usage_megabytes():
return get_process_memory_usage_kilobytes()/1024
def get_memory_object():
return psutil.virtual_memory() | en | 0.878427 | # # All or portions of this file Copyright (c) Amazon.com, Inc. or its affiliates or # its licensors. # # For complete copyright and license terms please see the LICENSE at the root of this # distribution (the "License"). All use of this software is governed by the License, # or, if provided, by the license below or the license accompanying this file. Do not # remove or modify any license notices. This file is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # | 2.367469 | 2 |
ippa/proc/__init__.py | PatientPathwayAnalysis/IPPA-py | 1 | 6620641 | <reponame>PatientPathwayAnalysis/IPPA-py
from .relatedillness import RelatedIllness
| from .relatedillness import RelatedIllness | none | 1 | 1.088694 | 1 | |
hTools2.roboFontExt/lib/Scripts/current glyph/make points smooth.py | frankrolf/hTools2_extension | 2 | 6620642 | # [h] convert selected points to `smooth`
g = CurrentGlyph()
g.prepareUndo('convert to smooth')
for c in g:
for s in c:
for p in s.points:
if p not in s.offCurve and p.selected:
s.smooth = True
g.performUndo()
| # [h] convert selected points to `smooth`
g = CurrentGlyph()
g.prepareUndo('convert to smooth')
for c in g:
for s in c:
for p in s.points:
if p not in s.offCurve and p.selected:
s.smooth = True
g.performUndo()
| en | 0.592435 | # [h] convert selected points to `smooth` | 2.696688 | 3 |
app/api/routers/users.py | ari-hacks/infra-pipeline | 0 | 6620643 | from fastapi import APIRouter, Request, Response, Body, HTTPException,Header
from fastapi.responses import PlainTextResponse
router = APIRouter()
@router.get("/", status_code=200)
async def health():
return {"Message":'user endpoint'}
@router.get("/health-check", status_code=200)
async def health():
return {"Message":'healthy user endpoint'} | from fastapi import APIRouter, Request, Response, Body, HTTPException,Header
from fastapi.responses import PlainTextResponse
router = APIRouter()
@router.get("/", status_code=200)
async def health():
return {"Message":'user endpoint'}
@router.get("/health-check", status_code=200)
async def health():
return {"Message":'healthy user endpoint'} | none | 1 | 2.661938 | 3 | |
Achilles/label/urls.py | parshwa1999/Map-Segmentation | 5 | 6620644 | from django.urls import path
from label import views
#from label import processing
import os
urlpatterns = [
path('', views.index, name='index'),
path('home/', views.homepage, name='homepage'),
path('user_login/', views.user_login, name='user_login'),
path('development_tracker/', views.development_tracker, name='developmentTracker'),
path('qgis_support/', views.qgis_support, name='qgisSupport'),
path('labelme_support/', views.labelme_support, name='labelmeSupport'),
path('qgis_support_response/', views.qgis_response, name='qgisResponse'),
path('get_csv/', views.get_csv, name='getCsv'),
path('get_mask/', views.get_mask, name='getPng'),
path('get_json/', views.get_json, name='getJson'),
path('labelme_support_response/', views.labelme_response, name='labelmeResponse'),
path('development_tracker_response/', views.development_tracker_response, name='developmentTrackerResponse'),
]
| from django.urls import path
from label import views
#from label import processing
import os
urlpatterns = [
path('', views.index, name='index'),
path('home/', views.homepage, name='homepage'),
path('user_login/', views.user_login, name='user_login'),
path('development_tracker/', views.development_tracker, name='developmentTracker'),
path('qgis_support/', views.qgis_support, name='qgisSupport'),
path('labelme_support/', views.labelme_support, name='labelmeSupport'),
path('qgis_support_response/', views.qgis_response, name='qgisResponse'),
path('get_csv/', views.get_csv, name='getCsv'),
path('get_mask/', views.get_mask, name='getPng'),
path('get_json/', views.get_json, name='getJson'),
path('labelme_support_response/', views.labelme_response, name='labelmeResponse'),
path('development_tracker_response/', views.development_tracker_response, name='developmentTrackerResponse'),
]
| en | 0.253504 | #from label import processing | 1.814504 | 2 |
build/tests/test_code_generation.py | ExternalRepositories/ApprovalTests.cpp | 259 | 6620645 | <gh_stars>100-1000
import unittest
import pyperclip
from approvaltests.approvals import verify, verify_all
from scripts.code_generation import CppGeneration
from scripts.multiline_string_utilities import remove_indentation
from tests.helpers import diff_merge_reporter
# Convenience variable, so we can paste in code and run test_demo_convert_to_concatenation.
# This is at global scope to prevent PyCharm reformatting the indentation when we
# paste code in.
to_concatenated_string = 'your string here'
to_multiline_string = ('your string here')
class CodeGeneration:
@staticmethod
def convert_concatenation_to_multiline(content: str) -> str:
lines = content.splitlines()
code = "remove_indentation << f'''\n"
for line in lines:
code += line + '\n'
code += "'''"
return code
@staticmethod
def convert_string_to_concatenation(content: str) -> str:
lines = content.splitlines()
code = '('
for line in lines:
if '{' in line:
code += 'f'
code += f"'{line}\\n'\n"
code += ')'
return code
@staticmethod
def convert_string_to_joined_list(content: str) -> str:
lines = content.splitlines()
code = "'\\n'.join([\n"
for line in lines:
if '{' in line:
code += 'f'
code += f"'{line}',\n"
code += '])'
return code
class TestCodeGeneration(unittest.TestCase):
def test_convert_string_to_concatentation(self) -> None:
content = remove_indentation << '''
toc
## v.x.y.z
{self.old_feature_text()}
'''
result = CodeGeneration.convert_string_to_concatenation(content)
expected = remove_indentation << r"""
('\n'
'toc\n'
'\n'
'## v.x.y.z\n'
'\n'
f'{self.old_feature_text()}\n'
'\n'
)"""
self.assertEqual(expected, result)
def test_convert_string_to_joined_list(self) -> None:
content = remove_indentation << '''
toc
## v.x.y.z
{self.old_feature_text()}
'''
result = CodeGeneration.convert_string_to_joined_list(content)
expected = remove_indentation << r"""
'\n'.join([
'',
'toc',
'',
'## v.x.y.z',
'',
f'{self.old_feature_text()}',
'',
])"""
self.assertEqual(expected, result)
def test_concatentation_to_multiline(self) -> None:
input = ('\n'
'toc\n'
'\n'
'## v.x.y.z\n'
'\n'
'{self.old_feature_text()}\n'
'\n'
)
output = CodeGeneration.convert_concatenation_to_multiline(input)
verify(output, diff_merge_reporter)
def test_entry_point_for_convert_to_concatenation(self) -> None:
if to_concatenated_string != 'your string here':
pyperclip.copy(CodeGeneration.convert_string_to_concatenation(to_concatenated_string))
print("converted concatened text copied to clipboard")
def test_entry_point_for_convert_to_multiline(self) -> None:
if to_multiline_string != 'your string here':
code = CodeGeneration.convert_concatenation_to_multiline(to_multiline_string)
print(code)
pyperclip.copy(code)
print("converted multiline text copied to clipboard")
def test_validate_single_header_file_content(self) -> None:
hs = ["A.h", "B.h"]
hpps = ["C.hpp"]
source_code_snippets = [
remove_indentation <<
'''
# Source code is fine: there should be no error message
#include <iostream>
#include "A.h"
#include "B.h"
''',
remove_indentation <<
'''
# A.h is incorrectly included
#include <A.h>
#include "B.h"
''',
remove_indentation <<
'''
# B.h and C.hpp are incorrectly included: there should ve error messages for both
#include <B.h>
#include <C.hpp>
''',
]
header = f"Testing validation of #include lines, with these header files: {str(hs)} and {str(hpps)}"
def validate_includes(source: str) -> str:
return f"""===============================\nSource snippet:\n{source}\n=>\nError message (if any):\n{CppGeneration.validate_single_header_file_content(hs, hpps, source)}"""
verify_all(
header,
source_code_snippets,
lambda source: validate_includes(source))
if __name__ == '__main__':
unittest.main()
| import unittest
import pyperclip
from approvaltests.approvals import verify, verify_all
from scripts.code_generation import CppGeneration
from scripts.multiline_string_utilities import remove_indentation
from tests.helpers import diff_merge_reporter
# Convenience variable, so we can paste in code and run test_demo_convert_to_concatenation.
# This is at global scope to prevent PyCharm reformatting the indentation when we
# paste code in.
to_concatenated_string = 'your string here'
to_multiline_string = ('your string here')
class CodeGeneration:
@staticmethod
def convert_concatenation_to_multiline(content: str) -> str:
lines = content.splitlines()
code = "remove_indentation << f'''\n"
for line in lines:
code += line + '\n'
code += "'''"
return code
@staticmethod
def convert_string_to_concatenation(content: str) -> str:
lines = content.splitlines()
code = '('
for line in lines:
if '{' in line:
code += 'f'
code += f"'{line}\\n'\n"
code += ')'
return code
@staticmethod
def convert_string_to_joined_list(content: str) -> str:
lines = content.splitlines()
code = "'\\n'.join([\n"
for line in lines:
if '{' in line:
code += 'f'
code += f"'{line}',\n"
code += '])'
return code
class TestCodeGeneration(unittest.TestCase):
def test_convert_string_to_concatentation(self) -> None:
content = remove_indentation << '''
toc
## v.x.y.z
{self.old_feature_text()}
'''
result = CodeGeneration.convert_string_to_concatenation(content)
expected = remove_indentation << r"""
('\n'
'toc\n'
'\n'
'## v.x.y.z\n'
'\n'
f'{self.old_feature_text()}\n'
'\n'
)"""
self.assertEqual(expected, result)
def test_convert_string_to_joined_list(self) -> None:
content = remove_indentation << '''
toc
## v.x.y.z
{self.old_feature_text()}
'''
result = CodeGeneration.convert_string_to_joined_list(content)
expected = remove_indentation << r"""
'\n'.join([
'',
'toc',
'',
'## v.x.y.z',
'',
f'{self.old_feature_text()}',
'',
])"""
self.assertEqual(expected, result)
def test_concatentation_to_multiline(self) -> None:
input = ('\n'
'toc\n'
'\n'
'## v.x.y.z\n'
'\n'
'{self.old_feature_text()}\n'
'\n'
)
output = CodeGeneration.convert_concatenation_to_multiline(input)
verify(output, diff_merge_reporter)
def test_entry_point_for_convert_to_concatenation(self) -> None:
if to_concatenated_string != 'your string here':
pyperclip.copy(CodeGeneration.convert_string_to_concatenation(to_concatenated_string))
print("converted concatened text copied to clipboard")
def test_entry_point_for_convert_to_multiline(self) -> None:
if to_multiline_string != 'your string here':
code = CodeGeneration.convert_concatenation_to_multiline(to_multiline_string)
print(code)
pyperclip.copy(code)
print("converted multiline text copied to clipboard")
def test_validate_single_header_file_content(self) -> None:
hs = ["A.h", "B.h"]
hpps = ["C.hpp"]
source_code_snippets = [
remove_indentation <<
'''
# Source code is fine: there should be no error message
#include <iostream>
#include "A.h"
#include "B.h"
''',
remove_indentation <<
'''
# A.h is incorrectly included
#include <A.h>
#include "B.h"
''',
remove_indentation <<
'''
# B.h and C.hpp are incorrectly included: there should ve error messages for both
#include <B.h>
#include <C.hpp>
''',
]
header = f"Testing validation of #include lines, with these header files: {str(hs)} and {str(hpps)}"
def validate_includes(source: str) -> str:
return f"""===============================\nSource snippet:\n{source}\n=>\nError message (if any):\n{CppGeneration.validate_single_header_file_content(hs, hpps, source)}"""
verify_all(
header,
source_code_snippets,
lambda source: validate_includes(source))
if __name__ == '__main__':
unittest.main() | en | 0.530381 | # Convenience variable, so we can paste in code and run test_demo_convert_to_concatenation. # This is at global scope to prevent PyCharm reformatting the indentation when we # paste code in. \n" for line in lines: code += line + '\n' code += " toc ## v.x.y.z {self.old_feature_text()} ('\n' 'toc\n' '\n' '## v.x.y.z\n' '\n' f'{self.old_feature_text()}\n' '\n' ) toc ## v.x.y.z {self.old_feature_text()} '\n'.join([ '', 'toc', '', '## v.x.y.z', '', f'{self.old_feature_text()}', '', ]) # v.x.y.z\n' # Source code is fine: there should be no error message #include <iostream> #include "A.h" #include "B.h" # A.h is incorrectly included #include <A.h> #include "B.h" # B.h and C.hpp are incorrectly included: there should ve error messages for both #include <B.h> #include <C.hpp> #include lines, with these header files: {str(hs)} and {str(hpps)}" ===============================\nSource snippet:\n{source}\n=>\nError message (if any):\n{CppGeneration.validate_single_header_file_content(hs, hpps, source)} | 2.847451 | 3 |
hogwarts/data/readers/ceph_reader.py | PingchuanMa/hogwarts | 4 | 6620646 | <reponame>PingchuanMa/hogwarts<filename>hogwarts/data/readers/ceph_reader.py
__all__ = ['CephReader']
import ceph
import glog
glog.setLevel(glog.logging.ERROR)
class CephReader:
def __call__(self, path):
s3client = ceph.S3Client()
content = s3client.Get(path)
return content
| __all__ = ['CephReader']
import ceph
import glog
glog.setLevel(glog.logging.ERROR)
class CephReader:
def __call__(self, path):
s3client = ceph.S3Client()
content = s3client.Get(path)
return content | none | 1 | 2.053192 | 2 | |
backend/webapp/models.py | MehdiNV/hackzurich19-suisse-cheese | 0 | 6620647 | from django.db import models
# Create your models here.
class Articles(models.Model):
title = models.CharField(max_length=200, default=None)
timestamp = models.DateTimeField(default=None)
body = models.CharField(max_length=1000, default=None)
journal = models.CharField(max_length=200, default=None)
def __str__(self):
return self.title
| from django.db import models
# Create your models here.
class Articles(models.Model):
title = models.CharField(max_length=200, default=None)
timestamp = models.DateTimeField(default=None)
body = models.CharField(max_length=1000, default=None)
journal = models.CharField(max_length=200, default=None)
def __str__(self):
return self.title
| en | 0.963489 | # Create your models here. | 2.534593 | 3 |
util_kerasmodel_to_tensorflow-pb.py | galsh17/cartwheel_train | 32 | 6620648 | #-------------------------------------------------------------------------------#
# Utility to convert Keras model to Tensorflow's .PB (proto-binary) and then to
# Nvidia libnvinfer's uff format. With UFF one can execute models on
# TensorRT compatible devices like TX2.
#
# Author : <NAME> <<EMAIL>>
# Created: 29th May, 2019
# Site : https://kusemanohar.wordpress.com/2019/05/25/hands-on-tensorrt-on-nvidiatx2/
#-------------------------------------------------------------------------------#
import keras
import numpy as np
import os
import tensorflow as tf
from CustomNets import NetVLADLayer, GhostVLADLayer
from predict_utils import change_model_inputshape
from keras import backend as K
import TerminalColors
tcol = TerminalColors.bcolors()
import argparse
def load_keras_hdf5_model( kerasmodel_h5file, verbose=True ):
""" Loads keras model from a HDF5 file """
assert os.path.isfile( kerasmodel_h5file ), 'The model weights file doesnot exists or there is a permission issue.'+"kerasmodel_file="+kerasmodel_h5file
K.set_learning_phase(0)
model = keras.models.load_model(kerasmodel_h5file, custom_objects={'NetVLADLayer': NetVLADLayer, 'GhostVLADLayer': GhostVLADLayer} )
if verbose:
model.summary();
print tcol.OKGREEN, 'Successfully Loaded kerasmodel_h5file: ', tcol.ENDC, kerasmodel_h5file
return model
def load_basic_model( ):
K.set_learning_phase(0)
from CustomNets import make_from_mobilenet, make_from_vgg16
from CustomNets import NetVLADLayer, GhostVLADLayer
# Please choose only one of these.
if False: # VGG
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_vgg16( input_img, weights=None, layer_name='block5_pool', kernel_regularizer=keras.regularizers.l2(0.01) )
model = keras.models.Model( inputs=input_img, outputs=cnn )
if True: #mobilenet
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_mobilenet( input_img, layer_name='conv_pw_5_relu', weights=None, kernel_regularizer=keras.regularizers.l2(0.01) )
model = keras.models.Model( inputs=input_img, outputs=cnn )
if False: #mobilenet+netvlad
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_mobilenet( input_img, layer_name='conv_pw_5_relu', weights=None, kernel_regularizer=keras.regularizers.l2(0.01) )
# cnn = make_from_vgg16( input_img, weights=None, layer_name='block5_pool', kernel_regularizer=keras.regularizers.l2(0.01) )
out = NetVLADLayer(num_clusters = 16)( cnn )
model = keras.models.Model( inputs=input_img, outputs=out )
if False: #netvlad only
input_img = keras.layers.Input( shape=(60, 80, 256 ) )
out = NetVLADLayer(num_clusters = 16)( input_img )
model = keras.models.Model( inputs=input_img, outputs=out )
model.summary()
return model
def write_kerasmodel_as_tensorflow_pb( model, LOG_DIR, output_model_name='output_model.pb' ):
""" Takes as input a keras.models.Model() and writes out
Tensorflow proto-binary.
"""
print tcol.HEADER,'[write_kerasmodel_as_tensorflow_pb] Start', tcol.ENDC
import tensorflow as tf
from tensorflow.python.framework import graph_util
from tensorflow.python.framework import graph_io
K.set_learning_phase(0)
sess = K.get_session()
# Make const
print 'Make Computation Graph as Constant and Prune unnecessary stuff from it'
constant_graph = graph_util.convert_variables_to_constants(
sess,
sess.graph.as_graph_def(),
[node.op.name for node in model.outputs])
constant_graph = tf.graph_util.remove_training_nodes(constant_graph)
#--- convert Switch --> Identity
# I am doing this because TensorRT cannot process Switch operations.
# # https://github.com/tensorflow/tensorflow/issues/8404#issuecomment-297469468
# for node in constant_graph.node:
# if node.op == "Switch":
# node.op = "Identity"
# del node.input[1]
# # END
# Write .pb
# output_model_name = 'output_model.pb'
print tcol.OKGREEN, 'Write ', output_model_name, tcol.ENDC
print 'model.outputs=', [node.op.name for node in model.outputs]
graph_io.write_graph(constant_graph, LOG_DIR, output_model_name,
as_text=False)
print tcol.HEADER, '[write_kerasmodel_as_tensorflow_pb] Done', tcol.ENDC
# Write .pbtxt (for viz only)
output_model_pbtxt_name = output_model_name+'.pbtxt' #'output_model.pbtxt'
print tcol.OKGREEN, 'Write ', output_model_pbtxt_name, tcol.ENDC
tf.train.write_graph(constant_graph, LOG_DIR,
output_model_pbtxt_name, as_text=True)
# Write model.summary to file (to get info on input and output shapes)
output_modelsummary_fname = LOG_DIR+'/'+output_model_name + '.modelsummary.log'
print tcol.OKGREEN, 'Write ', output_modelsummary_fname, tcol.ENDC
with open(output_modelsummary_fname,'w') as fh:
# Pass the file handle in as a lambda function to make it callable
model.summary(print_fn=lambda x: fh.write(x + '\n'))
if __name__ == '__main__':
#---
# Parse Command line
parser = argparse.ArgumentParser(description='Convert Keras hdf5 models to .uff models for TensorRT.')
parser.add_argument('--kerasmodel_h5file', '-h5', required=True, type=str, help='The input keras modelarch_and_weights full filename')
args = parser.parse_args()
#---
# Paths, File Init and other initialize
# kerasmodel_h5file = 'models.keras/June2019/centeredinput-m1to1-240x320x3__mobilenet-conv_pw_6_relu__K16__allpairloss/modelarch_and_weights.700.h5'
kerasmodel_h5file = args.kerasmodel_h5file
LOG_DIR = '/'.join( kerasmodel_h5file.split('/')[0:-1] )
print tcol.HEADER
print '##------------------------------------------------------------##'
print '## kerasmodel_h5file = ', kerasmodel_h5file
print '## LOG_DIR = ', LOG_DIR
print '##------------------------------------------------------------##'
print tcol.ENDC
#---
# Load HDF5 Keras model
model = load_keras_hdf5_model( kerasmodel_h5file, verbose=True ) #this
# model = load_basic_model()
# quit()
#-----
# Replace Input Layer's Dimensions
im_rows = None#480
im_cols = 752
im_chnls = 3
if im_rows == None or im_cols == None or im_chnls == None:
print tcol.WARNING, 'NOT doing `change_model_inputshape`', tcol.ENDC
new_model = model
else:
# change_model_inputshape uses model_from_json internally, I feel a bit uncomfortable about this.
new_model = change_model_inputshape( model, new_input_shape=(1,im_rows,im_cols,im_chnls), verbose=True )
print 'OLD MODEL: ', 'input_shape=', str(model.inputs)
print 'NEW MODEL: input_shape=', str(new_model.inputs)
#-----
# Write Tensorflow (atleast 1.12) proto-binary (.pb)
# write_kerasmodel_as_tensorflow_pb( new_model, LOG_DIR=LOG_DIR, output_model_name='output_model.pb' )
out_pb_fname = '.'.join( (kerasmodel_h5file.split('/')[-1]).split('.')[:-1] )+'.pb'
write_kerasmodel_as_tensorflow_pb( new_model, LOG_DIR=LOG_DIR, output_model_name=out_pb_fname )
| #-------------------------------------------------------------------------------#
# Utility to convert Keras model to Tensorflow's .PB (proto-binary) and then to
# Nvidia libnvinfer's uff format. With UFF one can execute models on
# TensorRT compatible devices like TX2.
#
# Author : <NAME> <<EMAIL>>
# Created: 29th May, 2019
# Site : https://kusemanohar.wordpress.com/2019/05/25/hands-on-tensorrt-on-nvidiatx2/
#-------------------------------------------------------------------------------#
import keras
import numpy as np
import os
import tensorflow as tf
from CustomNets import NetVLADLayer, GhostVLADLayer
from predict_utils import change_model_inputshape
from keras import backend as K
import TerminalColors
tcol = TerminalColors.bcolors()
import argparse
def load_keras_hdf5_model( kerasmodel_h5file, verbose=True ):
""" Loads keras model from a HDF5 file """
assert os.path.isfile( kerasmodel_h5file ), 'The model weights file doesnot exists or there is a permission issue.'+"kerasmodel_file="+kerasmodel_h5file
K.set_learning_phase(0)
model = keras.models.load_model(kerasmodel_h5file, custom_objects={'NetVLADLayer': NetVLADLayer, 'GhostVLADLayer': GhostVLADLayer} )
if verbose:
model.summary();
print tcol.OKGREEN, 'Successfully Loaded kerasmodel_h5file: ', tcol.ENDC, kerasmodel_h5file
return model
def load_basic_model( ):
K.set_learning_phase(0)
from CustomNets import make_from_mobilenet, make_from_vgg16
from CustomNets import NetVLADLayer, GhostVLADLayer
# Please choose only one of these.
if False: # VGG
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_vgg16( input_img, weights=None, layer_name='block5_pool', kernel_regularizer=keras.regularizers.l2(0.01) )
model = keras.models.Model( inputs=input_img, outputs=cnn )
if True: #mobilenet
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_mobilenet( input_img, layer_name='conv_pw_5_relu', weights=None, kernel_regularizer=keras.regularizers.l2(0.01) )
model = keras.models.Model( inputs=input_img, outputs=cnn )
if False: #mobilenet+netvlad
input_img = keras.layers.Input( shape=(240, 320, 3 ) )
cnn = make_from_mobilenet( input_img, layer_name='conv_pw_5_relu', weights=None, kernel_regularizer=keras.regularizers.l2(0.01) )
# cnn = make_from_vgg16( input_img, weights=None, layer_name='block5_pool', kernel_regularizer=keras.regularizers.l2(0.01) )
out = NetVLADLayer(num_clusters = 16)( cnn )
model = keras.models.Model( inputs=input_img, outputs=out )
if False: #netvlad only
input_img = keras.layers.Input( shape=(60, 80, 256 ) )
out = NetVLADLayer(num_clusters = 16)( input_img )
model = keras.models.Model( inputs=input_img, outputs=out )
model.summary()
return model
def write_kerasmodel_as_tensorflow_pb( model, LOG_DIR, output_model_name='output_model.pb' ):
""" Takes as input a keras.models.Model() and writes out
Tensorflow proto-binary.
"""
print tcol.HEADER,'[write_kerasmodel_as_tensorflow_pb] Start', tcol.ENDC
import tensorflow as tf
from tensorflow.python.framework import graph_util
from tensorflow.python.framework import graph_io
K.set_learning_phase(0)
sess = K.get_session()
# Make const
print 'Make Computation Graph as Constant and Prune unnecessary stuff from it'
constant_graph = graph_util.convert_variables_to_constants(
sess,
sess.graph.as_graph_def(),
[node.op.name for node in model.outputs])
constant_graph = tf.graph_util.remove_training_nodes(constant_graph)
#--- convert Switch --> Identity
# I am doing this because TensorRT cannot process Switch operations.
# # https://github.com/tensorflow/tensorflow/issues/8404#issuecomment-297469468
# for node in constant_graph.node:
# if node.op == "Switch":
# node.op = "Identity"
# del node.input[1]
# # END
# Write .pb
# output_model_name = 'output_model.pb'
print tcol.OKGREEN, 'Write ', output_model_name, tcol.ENDC
print 'model.outputs=', [node.op.name for node in model.outputs]
graph_io.write_graph(constant_graph, LOG_DIR, output_model_name,
as_text=False)
print tcol.HEADER, '[write_kerasmodel_as_tensorflow_pb] Done', tcol.ENDC
# Write .pbtxt (for viz only)
output_model_pbtxt_name = output_model_name+'.pbtxt' #'output_model.pbtxt'
print tcol.OKGREEN, 'Write ', output_model_pbtxt_name, tcol.ENDC
tf.train.write_graph(constant_graph, LOG_DIR,
output_model_pbtxt_name, as_text=True)
# Write model.summary to file (to get info on input and output shapes)
output_modelsummary_fname = LOG_DIR+'/'+output_model_name + '.modelsummary.log'
print tcol.OKGREEN, 'Write ', output_modelsummary_fname, tcol.ENDC
with open(output_modelsummary_fname,'w') as fh:
# Pass the file handle in as a lambda function to make it callable
model.summary(print_fn=lambda x: fh.write(x + '\n'))
if __name__ == '__main__':
#---
# Parse Command line
parser = argparse.ArgumentParser(description='Convert Keras hdf5 models to .uff models for TensorRT.')
parser.add_argument('--kerasmodel_h5file', '-h5', required=True, type=str, help='The input keras modelarch_and_weights full filename')
args = parser.parse_args()
#---
# Paths, File Init and other initialize
# kerasmodel_h5file = 'models.keras/June2019/centeredinput-m1to1-240x320x3__mobilenet-conv_pw_6_relu__K16__allpairloss/modelarch_and_weights.700.h5'
kerasmodel_h5file = args.kerasmodel_h5file
LOG_DIR = '/'.join( kerasmodel_h5file.split('/')[0:-1] )
print tcol.HEADER
print '##------------------------------------------------------------##'
print '## kerasmodel_h5file = ', kerasmodel_h5file
print '## LOG_DIR = ', LOG_DIR
print '##------------------------------------------------------------##'
print tcol.ENDC
#---
# Load HDF5 Keras model
model = load_keras_hdf5_model( kerasmodel_h5file, verbose=True ) #this
# model = load_basic_model()
# quit()
#-----
# Replace Input Layer's Dimensions
im_rows = None#480
im_cols = 752
im_chnls = 3
if im_rows == None or im_cols == None or im_chnls == None:
print tcol.WARNING, 'NOT doing `change_model_inputshape`', tcol.ENDC
new_model = model
else:
# change_model_inputshape uses model_from_json internally, I feel a bit uncomfortable about this.
new_model = change_model_inputshape( model, new_input_shape=(1,im_rows,im_cols,im_chnls), verbose=True )
print 'OLD MODEL: ', 'input_shape=', str(model.inputs)
print 'NEW MODEL: input_shape=', str(new_model.inputs)
#-----
# Write Tensorflow (atleast 1.12) proto-binary (.pb)
# write_kerasmodel_as_tensorflow_pb( new_model, LOG_DIR=LOG_DIR, output_model_name='output_model.pb' )
out_pb_fname = '.'.join( (kerasmodel_h5file.split('/')[-1]).split('.')[:-1] )+'.pb'
write_kerasmodel_as_tensorflow_pb( new_model, LOG_DIR=LOG_DIR, output_model_name=out_pb_fname )
| en | 0.472929 | #-------------------------------------------------------------------------------# # Utility to convert Keras model to Tensorflow's .PB (proto-binary) and then to # Nvidia libnvinfer's uff format. With UFF one can execute models on # TensorRT compatible devices like TX2. # # Author : <NAME> <<EMAIL>> # Created: 29th May, 2019 # Site : https://kusemanohar.wordpress.com/2019/05/25/hands-on-tensorrt-on-nvidiatx2/ #-------------------------------------------------------------------------------# Loads keras model from a HDF5 file # Please choose only one of these. # VGG #mobilenet #mobilenet+netvlad # cnn = make_from_vgg16( input_img, weights=None, layer_name='block5_pool', kernel_regularizer=keras.regularizers.l2(0.01) ) #netvlad only Takes as input a keras.models.Model() and writes out Tensorflow proto-binary. # Make const #--- convert Switch --> Identity # I am doing this because TensorRT cannot process Switch operations. # # https://github.com/tensorflow/tensorflow/issues/8404#issuecomment-297469468 # for node in constant_graph.node: # if node.op == "Switch": # node.op = "Identity" # del node.input[1] # # END # Write .pb # output_model_name = 'output_model.pb' # Write .pbtxt (for viz only) #'output_model.pbtxt' # Write model.summary to file (to get info on input and output shapes) # Pass the file handle in as a lambda function to make it callable #--- # Parse Command line #--- # Paths, File Init and other initialize # kerasmodel_h5file = 'models.keras/June2019/centeredinput-m1to1-240x320x3__mobilenet-conv_pw_6_relu__K16__allpairloss/modelarch_and_weights.700.h5' #------------------------------------------------------------##' # kerasmodel_h5file = ', kerasmodel_h5file # LOG_DIR = ', LOG_DIR #------------------------------------------------------------##' #--- # Load HDF5 Keras model #this # model = load_basic_model() # quit() #----- # Replace Input Layer's Dimensions #480 # change_model_inputshape uses model_from_json internally, I feel a bit uncomfortable about this. #----- # Write Tensorflow (atleast 1.12) proto-binary (.pb) # write_kerasmodel_as_tensorflow_pb( new_model, LOG_DIR=LOG_DIR, output_model_name='output_model.pb' ) | 2.554977 | 3 |
Homework2/scripts/cone_maker.py | Doruk-Coskun/ceng477-rasterization | 0 | 6620649 | <reponame>Doruk-Coskun/ceng477-rasterization
# author: <NAME>
# more info: https://github.com/arifgorkemozer/3dgeometricshapes/
import math
import sys
if len(sys.argv) < 8:
print "Usage: python cone_maker.py <cone_bottom_center_x>\n\t\t\t<cone_bottom_center_y>\n\t\t\t<cone_bottom_z_coord>\n\t\t\t<cone_top_distance>\n\t\t\t<cone_bottom_radius>\n\t\t\t<step_threshold>\n\t\t\t<last_vertex_id_in_3d_space>\n\t\t\t<color_primary: \"R|G|B\">\n\t\t\t<color_secondary: \"R|G|B\">\n\t\t\t<color_bottom_center: \"R|G|B\">\n\t\t\t<color_top: \"R|G|B\">"
else:
center_x = (float)(sys.argv[1])
center_y = (float)(sys.argv[2])
cone_bottom_z_coord = (float)(sys.argv[3])
cone_top_distance = (float)(sys.argv[4])
radius = (float)(sys.argv[5])
step_threshold = (float)(sys.argv[6])
last_vertex_id = (int)(sys.argv[7])
color_primary = None
color_secondary = None
color_cone_bottom_center = None
color_cone_top = None
if len(sys.argv) == 12:
color_primary_values = sys.argv[8].split("|")
color_secondary_values = sys.argv[9].split("|")
color_bottom_values = sys.argv[10].split("|")
color_top_values = sys.argv[11].split("|")
cpv = [int(n) for n in color_primary_values]
csv = [int(n) for n in color_secondary_values]
cbv = [int(n) for n in color_bottom_values]
ctv = [int(n) for n in color_top_values]
color_primary = tuple(cpv)
color_secondary = tuple(csv)
color_cone_bottom_center = tuple(cbv)
color_cone_top = tuple(ctv)
else:
color_primary = (255, 0, 0)
color_secondary = (0, 0, 255)
color_cone_bottom_center = (0, 255, 0)
color_cone_top = (0, 255, 255)
x = -radius
points = []
while x <= radius:
points.append( (x, math.sqrt(radius**2 - x**2), cone_bottom_z_coord) )
x += step_threshold
points_inv = points[::-1]
for elem in points_inv[1:]:
points.append( (elem[0], -elem[1], elem[2]) )
# add bottom center
points.append( (center_x, center_y, cone_bottom_z_coord) )
# add cone top
points.append( (center_x, center_y, cone_bottom_z_coord - cone_top_distance) )
triangles = []
front_last_vertex_id = len(points)-2
front_center_id = len(points)-1
back_center_id = len(points)
# cone bottom triangles (to cone bottom center)
for i in range(1, front_last_vertex_id):
triangles.append( (front_center_id +last_vertex_id, i+1 +last_vertex_id, i +last_vertex_id) )
# cone side triangles (to cone top)
for i in range(1, front_last_vertex_id):
triangles.append( (back_center_id +last_vertex_id, i +last_vertex_id, i+1 +last_vertex_id ) )
colors = []
for i in range(1, front_last_vertex_id+1):
if i % 2 == 1:
colors.append( color_primary )
else:
colors.append( color_secondary )
colors.append(color_cone_bottom_center)
colors.append(color_cone_top)
print "Colors:"
for c in colors:
print c[0], c[1], c[2]
print "Positions:", len(points)
for elem in points:
print elem[0], elem[1], elem[2]
print "Triangles:", len(triangles)
for tri in triangles:
print tri[0], tri[1], tri[2]
print len(points), "points created"
print len(triangles), "triangles created"
# write to a 3d scene file
with open("cone_scene.txt", 'w') as f:
f.write("100 100 100")
f.write("\n")
f.write("1")
f.write("\n")
f.write("#Vertices")
f.write("\n")
f.write(str(len(points)))
f.write("\n")
f.write("#Colors")
f.write("\n")
for c in colors:
f.write( str(c[0]) + " " + str(c[1]) + " " + str(c[2]))
f.write("\n")
f.write("#Positions")
f.write("\n")
for elem in points:
f.write( str(elem[0]) + " " + str(elem[1]) + " " + str(elem[2]))
f.write("\n")
f.write("#Translations")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Scalings")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Rotations")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Models")
f.write("\n")
f.write("1")
f.write("\n")
f.write("1")
f.write("\n")
f.write("1")
f.write("\n")
f.write("0")
f.write("\n")
f.write(str(len(triangles)))
f.write("\n")
for tri in triangles:
f.write( str(tri[0]) + " " + str(tri[1]) + " " + str(tri[2]))
f.write("\n")
| # author: <NAME>
# more info: https://github.com/arifgorkemozer/3dgeometricshapes/
import math
import sys
if len(sys.argv) < 8:
print "Usage: python cone_maker.py <cone_bottom_center_x>\n\t\t\t<cone_bottom_center_y>\n\t\t\t<cone_bottom_z_coord>\n\t\t\t<cone_top_distance>\n\t\t\t<cone_bottom_radius>\n\t\t\t<step_threshold>\n\t\t\t<last_vertex_id_in_3d_space>\n\t\t\t<color_primary: \"R|G|B\">\n\t\t\t<color_secondary: \"R|G|B\">\n\t\t\t<color_bottom_center: \"R|G|B\">\n\t\t\t<color_top: \"R|G|B\">"
else:
center_x = (float)(sys.argv[1])
center_y = (float)(sys.argv[2])
cone_bottom_z_coord = (float)(sys.argv[3])
cone_top_distance = (float)(sys.argv[4])
radius = (float)(sys.argv[5])
step_threshold = (float)(sys.argv[6])
last_vertex_id = (int)(sys.argv[7])
color_primary = None
color_secondary = None
color_cone_bottom_center = None
color_cone_top = None
if len(sys.argv) == 12:
color_primary_values = sys.argv[8].split("|")
color_secondary_values = sys.argv[9].split("|")
color_bottom_values = sys.argv[10].split("|")
color_top_values = sys.argv[11].split("|")
cpv = [int(n) for n in color_primary_values]
csv = [int(n) for n in color_secondary_values]
cbv = [int(n) for n in color_bottom_values]
ctv = [int(n) for n in color_top_values]
color_primary = tuple(cpv)
color_secondary = tuple(csv)
color_cone_bottom_center = tuple(cbv)
color_cone_top = tuple(ctv)
else:
color_primary = (255, 0, 0)
color_secondary = (0, 0, 255)
color_cone_bottom_center = (0, 255, 0)
color_cone_top = (0, 255, 255)
x = -radius
points = []
while x <= radius:
points.append( (x, math.sqrt(radius**2 - x**2), cone_bottom_z_coord) )
x += step_threshold
points_inv = points[::-1]
for elem in points_inv[1:]:
points.append( (elem[0], -elem[1], elem[2]) )
# add bottom center
points.append( (center_x, center_y, cone_bottom_z_coord) )
# add cone top
points.append( (center_x, center_y, cone_bottom_z_coord - cone_top_distance) )
triangles = []
front_last_vertex_id = len(points)-2
front_center_id = len(points)-1
back_center_id = len(points)
# cone bottom triangles (to cone bottom center)
for i in range(1, front_last_vertex_id):
triangles.append( (front_center_id +last_vertex_id, i+1 +last_vertex_id, i +last_vertex_id) )
# cone side triangles (to cone top)
for i in range(1, front_last_vertex_id):
triangles.append( (back_center_id +last_vertex_id, i +last_vertex_id, i+1 +last_vertex_id ) )
colors = []
for i in range(1, front_last_vertex_id+1):
if i % 2 == 1:
colors.append( color_primary )
else:
colors.append( color_secondary )
colors.append(color_cone_bottom_center)
colors.append(color_cone_top)
print "Colors:"
for c in colors:
print c[0], c[1], c[2]
print "Positions:", len(points)
for elem in points:
print elem[0], elem[1], elem[2]
print "Triangles:", len(triangles)
for tri in triangles:
print tri[0], tri[1], tri[2]
print len(points), "points created"
print len(triangles), "triangles created"
# write to a 3d scene file
with open("cone_scene.txt", 'w') as f:
f.write("100 100 100")
f.write("\n")
f.write("1")
f.write("\n")
f.write("#Vertices")
f.write("\n")
f.write(str(len(points)))
f.write("\n")
f.write("#Colors")
f.write("\n")
for c in colors:
f.write( str(c[0]) + " " + str(c[1]) + " " + str(c[2]))
f.write("\n")
f.write("#Positions")
f.write("\n")
for elem in points:
f.write( str(elem[0]) + " " + str(elem[1]) + " " + str(elem[2]))
f.write("\n")
f.write("#Translations")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Scalings")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Rotations")
f.write("\n")
f.write("0")
f.write("\n")
f.write("#Models")
f.write("\n")
f.write("1")
f.write("\n")
f.write("1")
f.write("\n")
f.write("1")
f.write("\n")
f.write("0")
f.write("\n")
f.write(str(len(triangles)))
f.write("\n")
for tri in triangles:
f.write( str(tri[0]) + " " + str(tri[1]) + " " + str(tri[2]))
f.write("\n") | en | 0.682237 | # author: <NAME> # more info: https://github.com/arifgorkemozer/3dgeometricshapes/ # add bottom center # add cone top # cone bottom triangles (to cone bottom center) # cone side triangles (to cone top) # write to a 3d scene file | 2.561173 | 3 |
tests/unit/utils/test_file_hash.py | blade2005/runway | 134 | 6620650 | <reponame>blade2005/runway<gh_stars>100-1000
"""Test runway.utils._file_hash."""
# pylint: disable=no-self-use
# pyright: basic
from __future__ import annotations
import hashlib
from typing import TYPE_CHECKING
import pytest
from runway.utils._file_hash import FileHash
if TYPE_CHECKING:
from pathlib import Path
MODULE = "runway.utils._file_hash"
ALGS_TO_TEST = ["md5", "sha256"]
class TestFileHash:
"""Test FileHash."""
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
content = "hello world!"
expected = hashlib.new(alg)
expected.update(content.encode())
test_file = tmp_path / "test.txt"
test_file.write_text(content)
result = FileHash(hashlib.new(alg))
result.add_file(test_file)
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file_name(self, alg: str, tmp_path: Path) -> None:
"""Test add_file_name."""
test_file = tmp_path / "test.txt"
test_file.resolve()
expected = hashlib.new(alg)
expected.update((str(test_file) + "\0").encode())
result_path = FileHash(hashlib.new(alg))
result_path.add_file_name(test_file)
assert result_path.digest_size == expected.digest_size
assert result_path.digest == expected.digest()
assert result_path.hexdigest == expected.hexdigest()
result_str = FileHash(hashlib.new(alg))
result_str.add_file_name(str(test_file))
assert result_str.digest_size == expected.digest_size
assert result_str.digest == expected.digest()
assert result_str.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file_name_relative(self, alg: str, tmp_path: Path) -> None:
"""Test add_file_name."""
tld = tmp_path.parents[0]
test_file = tmp_path / "test.txt"
test_file.resolve()
expected = hashlib.new(alg)
expected.update((str(test_file.relative_to(tld)) + "\0").encode())
result_path = FileHash(hashlib.new(alg))
result_path.add_file_name(test_file, relative_to=tld)
assert result_path.digest_size == expected.digest_size
assert result_path.digest == expected.digest()
assert result_path.hexdigest == expected.hexdigest()
result_str = FileHash(hashlib.new(alg))
result_str.add_file_name(str(test_file), relative_to=tld)
assert result_str.digest_size == expected.digest_size
assert result_str.digest == expected.digest()
assert result_str.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_files(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
content = "hello world!"
test_file0 = tmp_path / "test0.txt"
test_file0.write_text(content)
test_file1 = tmp_path / "test1.txt"
test_file1.write_text(content)
expected = hashlib.new(alg)
for test_file in [test_file0, test_file1]:
expected.update((str(test_file) + "\0").encode())
expected.update((content + "\0").encode())
result = FileHash(hashlib.new(alg))
result.add_files([test_file0, test_file1])
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_files_relative(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
tld = tmp_path.parents[0]
content = "hello world!"
test_file0 = tmp_path / "test0.txt"
test_file0.write_text(content)
test_file1 = tmp_path / "test1.txt"
test_file1.write_text(content)
expected = hashlib.new(alg)
for test_file in [test_file0, test_file1]:
expected.update((str(test_file.relative_to(tld)) + "\0").encode())
expected.update((content + "\0").encode())
result = FileHash(hashlib.new(alg))
result.add_files([test_file0, test_file1], relative_to=tld)
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest()
| """Test runway.utils._file_hash."""
# pylint: disable=no-self-use
# pyright: basic
from __future__ import annotations
import hashlib
from typing import TYPE_CHECKING
import pytest
from runway.utils._file_hash import FileHash
if TYPE_CHECKING:
from pathlib import Path
MODULE = "runway.utils._file_hash"
ALGS_TO_TEST = ["md5", "sha256"]
class TestFileHash:
"""Test FileHash."""
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
content = "hello world!"
expected = hashlib.new(alg)
expected.update(content.encode())
test_file = tmp_path / "test.txt"
test_file.write_text(content)
result = FileHash(hashlib.new(alg))
result.add_file(test_file)
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file_name(self, alg: str, tmp_path: Path) -> None:
"""Test add_file_name."""
test_file = tmp_path / "test.txt"
test_file.resolve()
expected = hashlib.new(alg)
expected.update((str(test_file) + "\0").encode())
result_path = FileHash(hashlib.new(alg))
result_path.add_file_name(test_file)
assert result_path.digest_size == expected.digest_size
assert result_path.digest == expected.digest()
assert result_path.hexdigest == expected.hexdigest()
result_str = FileHash(hashlib.new(alg))
result_str.add_file_name(str(test_file))
assert result_str.digest_size == expected.digest_size
assert result_str.digest == expected.digest()
assert result_str.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_file_name_relative(self, alg: str, tmp_path: Path) -> None:
"""Test add_file_name."""
tld = tmp_path.parents[0]
test_file = tmp_path / "test.txt"
test_file.resolve()
expected = hashlib.new(alg)
expected.update((str(test_file.relative_to(tld)) + "\0").encode())
result_path = FileHash(hashlib.new(alg))
result_path.add_file_name(test_file, relative_to=tld)
assert result_path.digest_size == expected.digest_size
assert result_path.digest == expected.digest()
assert result_path.hexdigest == expected.hexdigest()
result_str = FileHash(hashlib.new(alg))
result_str.add_file_name(str(test_file), relative_to=tld)
assert result_str.digest_size == expected.digest_size
assert result_str.digest == expected.digest()
assert result_str.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_files(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
content = "hello world!"
test_file0 = tmp_path / "test0.txt"
test_file0.write_text(content)
test_file1 = tmp_path / "test1.txt"
test_file1.write_text(content)
expected = hashlib.new(alg)
for test_file in [test_file0, test_file1]:
expected.update((str(test_file) + "\0").encode())
expected.update((content + "\0").encode())
result = FileHash(hashlib.new(alg))
result.add_files([test_file0, test_file1])
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest()
@pytest.mark.parametrize("alg", ALGS_TO_TEST)
def test_add_files_relative(self, alg: str, tmp_path: Path) -> None:
"""Test add_file."""
tld = tmp_path.parents[0]
content = "hello world!"
test_file0 = tmp_path / "test0.txt"
test_file0.write_text(content)
test_file1 = tmp_path / "test1.txt"
test_file1.write_text(content)
expected = hashlib.new(alg)
for test_file in [test_file0, test_file1]:
expected.update((str(test_file.relative_to(tld)) + "\0").encode())
expected.update((content + "\0").encode())
result = FileHash(hashlib.new(alg))
result.add_files([test_file0, test_file1], relative_to=tld)
assert result.digest_size == expected.digest_size
assert result.digest == expected.digest()
assert result.hexdigest == expected.hexdigest() | en | 0.581632 | Test runway.utils._file_hash. # pylint: disable=no-self-use # pyright: basic Test FileHash. Test add_file. Test add_file_name. Test add_file_name. Test add_file. Test add_file. | 2.429001 | 2 |