chore(release): 0.7.9

Reviewed-on: #37

CHANGELOG.md

@@ -2,6 +2,14 @@
 
 All notable changes to this project will be documented in this file. See [standard-version](https://github.com/conventional-changelog/standard-version) for commit guidelines.
 
+### [0.7.9](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.8...0.7.9) (2024-04-21)
+
+
+### Features
+
+* adds ability to write custom dmc filters ([ea080ca](https://gitea.deepak.science:2222/physics/deepdog/commit/ea080ca1c7068042ce1e0a222d317f785a6b05f4))
+* adds tarucha phase calculation, using spin qubit precession rate noise ([3ae0783](https://gitea.deepak.science:2222/physics/deepdog/commit/3ae0783d00cbe6a76439c1d671f2cff621d8d0a8))
+
 ### [0.7.8](https://gitea.deepak.science:2222/physics/deepdog/compare/0.7.7...0.7.8) (2024-02-29)
 
 

deepdog/direct_monte_carlo/compose_filter.py

@@ -0,0 +1,14 @@
+from typing import Sequence
+from deepdog.direct_monte_carlo.direct_mc import DirectMonteCarloFilter
+import numpy
+
+
+class ComposedDMCFilter(DirectMonteCarloFilter):
+	def __init__(self, filters: Sequence[DirectMonteCarloFilter]):
+		self.filters = filters
+
+	def filter_samples(self, samples: numpy.ndarray) -> numpy.ndarray:
+		current_sample = samples
+		for filter in self.filters:
+			current_sample = filter.filter_samples(current_sample)
+		return current_sample

deepdog/direct_monte_carlo/direct_mc.py

@@ -2,7 +2,7 @@ import pdme.model
 import pdme.measurement
 import pdme.measurement.input_types
 import pdme.subspace_simulation
-from typing import Tuple, Sequence
+from typing import Tuple, Dict, NewType, Any
 from dataclasses import dataclass
 import logging
 import numpy
@@ -30,6 +30,20 @@ class DirectMonteCarloConfig:
 	tag: str = ""
 
 
+# Aliasing dict as a generic data container
+DirectMonteCarloData = NewType("DirectMonteCarloData", Dict[str, Any])
+
+
+class DirectMonteCarloFilter:
+	"""
+	Abstract class for filtering out samples matching some criteria. Initialise with data as needed,
+	then filter out samples as needed.
+	"""
+
+	def filter_samples(self, samples: numpy.ndarray) -> numpy.ndarray:
+		raise NotImplementedError
+
+
 class DirectMonteCarloRun:
 	"""
 	A single model Direct Monte Carlo run, currently implemented only using single threading.
@@ -65,25 +79,26 @@ class DirectMonteCarloRun:
 	def __init__(
 		self,
 		model_name_pair: Tuple[str, pdme.model.DipoleModel],
-		measurements: Sequence[pdme.measurement.DotRangeMeasurement],
+		filter: DirectMonteCarloFilter,
 		config: DirectMonteCarloConfig,
 	):
 		self.model_name, self.model = model_name_pair
 
-		self.measurements = measurements
+		# self.measurements = measurements
-		self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
+		# self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
 
-		self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
+		# self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
-			self.dot_inputs
+		# 	self.dot_inputs
-		)
+		# )
 
 		self.config = config
-		(
+		self.filter = filter
-			self.lows,
+		# (
-			self.highs,
+		# 	self.lows,
-		) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
+		# 	self.highs,
-			self.measurements
+		# ) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
-		)
+		# 	self.measurements
+		# )
 
 	def _single_run(self, seed) -> numpy.ndarray:
 		rng = numpy.random.default_rng(seed)
@@ -93,18 +108,20 @@ class DirectMonteCarloRun:
 		)
 
 		current_sample = sample_dipoles
-		for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
 
-			if len(current_sample) < 1:
+		return self.filter.filter_samples(current_sample)
-				break
+		# for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
-			vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
-				numpy.array([di]), current_sample
-			)
 
-			current_sample = current_sample[
+		# 	if len(current_sample) < 1:
-				numpy.all((vals > low) & (vals < high), axis=1)
+		# 		break
-			]
+		# 	vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
-		return current_sample
+		# 		numpy.array([di]), current_sample
+		# 	)
+
+		# 	current_sample = current_sample[
+		# 		numpy.all((vals > low) & (vals < high), axis=1)
+		# 	]
+		# return current_sample
 
 	def execute(self) -> DirectMonteCarloResult:
 		step_count = 0

deepdog/direct_monte_carlo/dmc_filters.py

@@ -0,0 +1,143 @@
+from numpy import ndarray
+from deepdog.direct_monte_carlo.direct_mc import DirectMonteCarloFilter
+from typing import Sequence
+import pdme.measurement
+import pdme.measurement.input_types
+import pdme.util.fast_nonlocal_spectrum
+import pdme.util.fast_v_calc
+import numpy
+
+
+class SingleDotPotentialFilter(DirectMonteCarloFilter):
+	def __init__(self, measurements: Sequence[pdme.measurement.DotRangeMeasurement]):
+		self.measurements = measurements
+		self.dot_inputs = [(measure.r, measure.f) for measure in self.measurements]
+
+		self.dot_inputs_array = pdme.measurement.input_types.dot_inputs_to_array(
+			self.dot_inputs
+		)
+		(
+			self.lows,
+			self.highs,
+		) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
+			self.measurements
+		)
+
+	def filter_samples(self, samples: ndarray) -> ndarray:
+		current_sample = samples
+		for di, low, high in zip(self.dot_inputs_array, self.lows, self.highs):
+
+			if len(current_sample) < 1:
+				break
+			vals = pdme.util.fast_v_calc.fast_vs_for_dipoleses(
+				numpy.array([di]), current_sample
+			)
+
+			current_sample = current_sample[
+				numpy.all((vals > low) & (vals < high), axis=1)
+			]
+		return current_sample
+
+
+class DoubleDotSpinQubitFrequencyFilter(DirectMonteCarloFilter):
+	def __init__(
+		self,
+		pair_phase_measurements: Sequence[pdme.measurement.DotPairRangeMeasurement],
+	):
+		self.pair_phase_measurements = pair_phase_measurements
+		self.dot_pair_inputs = [
+			(measure.r1, measure.r2, measure.f)
+			for measure in self.pair_phase_measurements
+		]
+		self.dot_pair_inputs_array = (
+			pdme.measurement.input_types.dot_pair_inputs_to_array(self.dot_pair_inputs)
+		)
+		(
+			self.pair_phase_lows,
+			self.pair_phase_highs,
+		) = pdme.measurement.input_types.dot_range_measurements_low_high_arrays(
+			self.pair_phase_measurements
+		)
+
+	def fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
+		self, dot_pair_inputs: numpy.ndarray, dipoleses: numpy.ndarray
+	) -> numpy.ndarray:
+		"""
+		No error correction here baby.
+		"""
+		ps = dipoleses[:, :, 0:3]
+		ss = dipoleses[:, :, 3:6]
+		ws = dipoleses[:, :, 6]
+
+		r1s = dot_pair_inputs[:, 0, 0:3]
+		r2s = dot_pair_inputs[:, 1, 0:3]
+		f1s = dot_pair_inputs[:, 0, 3]
+		# Don't actually need this
+		# f2s = dot_pair_inputs[:, 1, 3]
+
+		diffses1 = r1s[:, None] - ss[:, None, :]
+		diffses2 = r2s[:, None] - ss[:, None, :]
+
+		norms1 = numpy.linalg.norm(diffses1, axis=3)
+		norms2 = numpy.linalg.norm(diffses2, axis=3)
+
+		alphses1 = (
+			(
+				3
+				* numpy.transpose(
+					numpy.transpose(
+						numpy.einsum("abcd,acd->abc", diffses1, ps) / (norms1**2)
+					)
+					* numpy.transpose(diffses1)
+				)[:, :, :, 0]
+			)
+			- ps[:, :, 0, numpy.newaxis]
+		) / (norms1**3)
+		alphses2 = (
+			(
+				3
+				* numpy.transpose(
+					numpy.transpose(
+						numpy.einsum("abcd,acd->abc", diffses2, ps) / (norms2**2)
+					)
+					* numpy.transpose(diffses2)
+				)[:, :, :, 0]
+			)
+			- ps[:, :, 0, numpy.newaxis]
+		) / (norms2**3)
+
+		bses = (1 / numpy.pi) * (
+			ws[:, None, :] / (f1s[:, None] ** 2 + ws[:, None, :] ** 2)
+		)
+
+		return numpy.einsum("...j->...", alphses1 * alphses2 * bses)
+
+	def filter_samples(self, samples: ndarray) -> ndarray:
+		current_sample = samples
+
+		for pi, plow, phigh in zip(
+			self.dot_pair_inputs_array, self.pair_phase_lows, self.pair_phase_highs
+		):
+			if len(current_sample) < 1:
+				break
+
+			###
+			# This should be  abstracted out, but we're going to dump it here for time pressure's sake
+			###
+			# vals = pdme.util.fast_nonlocal_spectrum.signarg(
+			# 	pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
+			# 		numpy.array([pi]), current_sample
+			# 	)
+			#
+			vals = pdme.util.fast_nonlocal_spectrum.signarg(
+				self.fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
+					numpy.array([pi]), current_sample
+				)
+			)
+			current_sample = current_sample[
+				numpy.all(
+					((vals > plow) & (vals < phigh)) | ((vals < plow) & (vals > phigh)),
+					axis=1,
+				)
+			]
+		return current_sample

deepdog/real_spectrum_run.py

@@ -66,7 +66,7 @@ def get_a_result_fast_filter_pairs(input) -> int:
 	return len(current_sample)
 
 
-def get_a_result_fast_filter_pair_phase_only(input) -> int:
+def get_a_result_fast_filter_potential_pair_phase_only(input) -> int:
 	(
 		model,
 		pair_inputs,
@@ -102,6 +102,103 @@ def get_a_result_fast_filter_pair_phase_only(input) -> int:
 	return len(current_sample)
 
 
+def get_a_result_fast_filter_tarucha_spin_qubit_pair_phase_only(input) -> int:
+	(
+		model,
+		pair_inputs,
+		pair_phase_lows,
+		pair_phase_highs,
+		monte_carlo_count,
+		seed,
+	) = input
+
+	def fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
+		dot_pair_inputs: numpy.ndarray, dipoleses: numpy.ndarray
+	) -> numpy.ndarray:
+		"""
+		No error correction here baby.
+		"""
+		ps = dipoleses[:, :, 0:3]
+		ss = dipoleses[:, :, 3:6]
+		ws = dipoleses[:, :, 6]
+
+		r1s = dot_pair_inputs[:, 0, 0:3]
+		r2s = dot_pair_inputs[:, 1, 0:3]
+		f1s = dot_pair_inputs[:, 0, 3]
+		# don't actually need, because we're assuming they're the same frequencies across the pair
+		# f2s = dot_pair_inputs[:, 1, 3]
+
+		diffses1 = r1s[:, None] - ss[:, None, :]
+		diffses2 = r2s[:, None] - ss[:, None, :]
+
+		norms1 = numpy.linalg.norm(diffses1, axis=3)
+		norms2 = numpy.linalg.norm(diffses2, axis=3)
+
+		alphses1 = (
+			(
+				3
+				* numpy.transpose(
+					numpy.transpose(
+						numpy.einsum("abcd,acd->abc", diffses1, ps) / (norms1**2)
+					)
+					* numpy.transpose(diffses1)
+				)[:, :, :, 0]
+			)
+			- ps[:, :, 0, numpy.newaxis]
+		) / (norms1**3)
+		alphses2 = (
+			(
+				3
+				* numpy.transpose(
+					numpy.transpose(
+						numpy.einsum("abcd,acd->abc", diffses2, ps) / (norms2**2)
+					)
+					* numpy.transpose(diffses2)
+				)[:, :, :, 0]
+			)
+			- ps[:, :, 0, numpy.newaxis]
+		) / (norms2**3)
+
+		bses = (1 / numpy.pi) * (
+			ws[:, None, :] / (f1s[:, None] ** 2 + ws[:, None, :] ** 2)
+		)
+
+		return numpy.einsum("...j->...", alphses1 * alphses2 * bses)
+
+	rng = numpy.random.default_rng(seed)
+	# TODO: A long term refactor is to pull the frequency stuff out from here. The None stands for max_frequency, which is unneeded in the actually useful models.
+	sample_dipoles = model.get_monte_carlo_dipole_inputs(
+		monte_carlo_count, None, rng_to_use=rng
+	)
+
+	current_sample = sample_dipoles
+
+	for pi, plow, phigh in zip(pair_inputs, pair_phase_lows, pair_phase_highs):
+		if len(current_sample) < 1:
+			break
+
+		###
+		# This should be  abstracted out, but we're going to dump it here for time pressure's sake
+		###
+		# vals = pdme.util.fast_nonlocal_spectrum.signarg(
+		# 	pdme.util.fast_nonlocal_spectrum.fast_s_nonlocal_dipoleses(
+		# 		numpy.array([pi]), current_sample
+		# 	)
+		#
+		vals = pdme.util.fast_nonlocal_spectrum.signarg(
+			fast_s_spin_qubit_tarucha_nonlocal_dipoleses(
+				numpy.array([pi]), current_sample
+			)
+		)
+		current_sample = current_sample[
+			numpy.all(
+				((vals > plow) & (vals < phigh)) | ((vals < plow) & (vals > phigh)),
+				axis=1,
+			)
+		]
+	return len(current_sample)
+
+
 def get_a_result_fast_filter(input) -> int:
 	model, dot_inputs, lows, highs, monte_carlo_count, seed = input
 
@@ -299,6 +396,7 @@ class RealSpectrumRun:
 					seeds = seed_sequence.spawn(self.monte_carlo_cycles)
 
 					if self.use_pair_measurements:
+						_logger.debug("using pair measurements")
 						current_success = sum(
 							pool.imap_unordered(
 								get_a_result_fast_filter_pairs,
@@ -320,9 +418,11 @@ class RealSpectrumRun:
 							)
 						)
 					elif self.use_pair_phase_measurements:
+						_logger.debug("using pair phase measurements")
+						_logger.debug("specifically using tarucha")
 						current_success = sum(
 							pool.imap_unordered(
-								get_a_result_fast_filter_pairs,
+								get_a_result_fast_filter_tarucha_spin_qubit_pair_phase_only,
 								[
 									(
 										model,

do.sh

@@ -1,38 +0,0 @@
-#!/usr/bin/env bash
-# Do - The Simplest Build Tool on Earth.
-# Documentation and examples see https://github.com/8gears/do
-
-set -Eeuo pipefail # -e "Automatic exit from bash shell script on error"  -u "Treat unset variables and parameters as errors"
-
-build() {
-   echo "I am ${FUNCNAME[0]}ing"
-   poetry build
-}
-
-test() {
-   echo "I am ${FUNCNAME[0]}ing"
-   poetry run flake8 deepdog tests
-   poetry run mypy deepdog
-   poetry run pytest
-}
-
-fmt() {
-	poetry run black .
-	find . -not \( -path "./.*" -type d -prune \) -type f -name "*.py" -exec sed -i -e 's/    /\t/g' {} \;
-}
-
-release() {
-   ./scripts/release.sh
-}
-
-htmlcov() {
-	poetry run pytest --cov-report=html
-}
-
-all() {
-   build && test
-}
-
-"$@" # <- execute the task
-
-[ "$#" -gt 0 ] || printf "Usage:\n\t./do.sh %s\n" "($(compgen -A function | grep '^[^_]' | paste -sd '|' -))"

flake.lock

@@ -1,28 +1,33 @@
 {
   "nodes": {
     "flake-utils": {
+      "inputs": {
+        "systems": "systems"
+      },
       "locked": {
-        "lastModified": 1648297722,
+        "lastModified": 1710146030,
-        "narHash": "sha256-W+qlPsiZd8F3XkzXOzAoR+mpFqzm3ekQkJNa+PIh1BQ=",
+        "narHash": "sha256-SZ5L6eA7HJ/nmkzGG7/ISclqe6oZdOZTNoesiInkXPQ=",
         "owner": "numtide",
         "repo": "flake-utils",
-        "rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
+        "rev": "b1d9ab70662946ef0850d488da1c9019f3a9752a",
         "type": "github"
       },
       "original": {
         "owner": "numtide",
         "repo": "flake-utils",
-        "rev": "0f8662f1319ad6abf89b3380dd2722369fc51ade",
         "type": "github"
       }
     },
     "flake-utils_2": {
+      "inputs": {
+        "systems": "systems_2"
+      },
       "locked": {
-        "lastModified": 1653893745,
+        "lastModified": 1705309234,
-        "narHash": "sha256-0jntwV3Z8//YwuOjzhV2sgJJPt+HY6KhU7VZUL0fKZQ=",
+        "narHash": "sha256-uNRRNRKmJyCRC/8y1RqBkqWBLM034y4qN7EprSdmgyA=",
         "owner": "numtide",
         "repo": "flake-utils",
-        "rev": "1ed9fb1935d260de5fe1c2f7ee0ebaae17ed2fa1",
+        "rev": "1ef2e671c3b0c19053962c07dbda38332dcebf26",
         "type": "github"
       },
       "original": {
@@ -31,29 +36,34 @@
         "type": "github"
       }
     },
+    "nix-github-actions": {
+      "inputs": {
+        "nixpkgs": [
+          "poetry2nixSrc",
+          "nixpkgs"
+        ]
+      },
+      "locked": {
+        "lastModified": 1703863825,
+        "narHash": "sha256-rXwqjtwiGKJheXB43ybM8NwWB8rO2dSRrEqes0S7F5Y=",
+        "owner": "nix-community",
+        "repo": "nix-github-actions",
+        "rev": "5163432afc817cf8bd1f031418d1869e4c9d5547",
+        "type": "github"
+      },
+      "original": {
+        "owner": "nix-community",
+        "repo": "nix-github-actions",
+        "type": "github"
+      }
+    },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1655087213,
+        "lastModified": 1710703777,
-        "narHash": "sha256-4R5oQ+OwGAAcXWYrxC4gFMTUSstGxaN8kN7e8hkum/8=",
+        "narHash": "sha256-M4CNAgjrtvrxIWIAc98RTYcVFoAgwUhrYekeiMScj18=",
         "owner": "NixOS",
         "repo": "nixpkgs",
-        "rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
+        "rev": "fc7885fbcea4b782142e06ce2d4d08cf92862004",
-        "type": "github"
-      },
-      "original": {
-        "owner": "NixOS",
-        "repo": "nixpkgs",
-        "rev": "37b6b161e536fddca54424cf80662bce735bdd1e",
-        "type": "github"
-      }
-    },
-    "nixpkgs_2": {
-      "locked": {
-        "lastModified": 1655046959,
-        "narHash": "sha256-gxqHZKq1ReLDe6ZMJSbmSZlLY95DsVq5o6jQihhzvmw=",
-        "owner": "NixOS",
-        "repo": "nixpkgs",
-        "rev": "07bf3d25ce1da3bee6703657e6a787a4c6cdcea9",
         "type": "github"
       },
       "original": {
@@ -62,23 +72,27 @@
         "type": "github"
       }
     },
-    "poetry2nix": {
+    "poetry2nixSrc": {
       "inputs": {
         "flake-utils": "flake-utils_2",
-        "nixpkgs": "nixpkgs_2"
+        "nix-github-actions": "nix-github-actions",
+        "nixpkgs": [
+          "nixpkgs"
+        ],
+        "systems": "systems_3",
+        "treefmt-nix": "treefmt-nix"
       },
       "locked": {
-        "lastModified": 1654921554,
+        "lastModified": 1708589824,
-        "narHash": "sha256-hkfMdQAHSwLWlg0sBVvgrQdIiBP45U1/ktmFpY4g2Mo=",
+        "narHash": "sha256-2GOiFTkvs5MtVF65sC78KNVxQSmsxtk0WmV1wJ9V2ck=",
         "owner": "nix-community",
         "repo": "poetry2nix",
-        "rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
+        "rev": "3c92540611f42d3fb2d0d084a6c694cd6544b609",
         "type": "github"
       },
       "original": {
         "owner": "nix-community",
         "repo": "poetry2nix",
-        "rev": "7b71679fa7df00e1678fc3f1d1d4f5f372341b63",
         "type": "github"
       }
     },
@@ -86,7 +100,72 @@
       "inputs": {
         "flake-utils": "flake-utils",
         "nixpkgs": "nixpkgs",
-        "poetry2nix": "poetry2nix"
+        "poetry2nixSrc": "poetry2nixSrc"
+      }
+    },
+    "systems": {
+      "locked": {
+        "lastModified": 1681028828,
+        "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
+        "owner": "nix-systems",
+        "repo": "default",
+        "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
+        "type": "github"
+      },
+      "original": {
+        "owner": "nix-systems",
+        "repo": "default",
+        "type": "github"
+      }
+    },
+    "systems_2": {
+      "locked": {
+        "lastModified": 1681028828,
+        "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
+        "owner": "nix-systems",
+        "repo": "default",
+        "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
+        "type": "github"
+      },
+      "original": {
+        "owner": "nix-systems",
+        "repo": "default",
+        "type": "github"
+      }
+    },
+    "systems_3": {
+      "locked": {
+        "lastModified": 1681028828,
+        "narHash": "sha256-Vy1rq5AaRuLzOxct8nz4T6wlgyUR7zLU309k9mBC768=",
+        "owner": "nix-systems",
+        "repo": "default",
+        "rev": "da67096a3b9bf56a91d16901293e51ba5b49a27e",
+        "type": "github"
+      },
+      "original": {
+        "id": "systems",
+        "type": "indirect"
+      }
+    },
+    "treefmt-nix": {
+      "inputs": {
+        "nixpkgs": [
+          "poetry2nixSrc",
+          "nixpkgs"
+        ]
+      },
+      "locked": {
+        "lastModified": 1708335038,
+        "narHash": "sha256-ETLZNFBVCabo7lJrpjD6cAbnE11eDOjaQnznmg/6hAE=",
+        "owner": "numtide",
+        "repo": "treefmt-nix",
+        "rev": "e504621290a1fd896631ddbc5e9c16f4366c9f65",
+        "type": "github"
+      },
+      "original": {
+        "owner": "numtide",
+        "repo": "treefmt-nix",
+        "type": "github"
       }
     }
   },

flake.nix

@@ -1,63 +1,46 @@
 {
   description = "Application packaged using poetry2nix";
 
-  inputs.flake-utils.url = "github:numtide/flake-utils?rev=0f8662f1319ad6abf89b3380dd2722369fc51ade";
+  inputs.flake-utils.url = "github:numtide/flake-utils";
-  inputs.nixpkgs.url = "github:NixOS/nixpkgs?rev=37b6b161e536fddca54424cf80662bce735bdd1e";
+  inputs.nixpkgs.url = "github:NixOS/nixpkgs";
-  inputs.poetry2nix.url = "github:nix-community/poetry2nix?rev=7b71679fa7df00e1678fc3f1d1d4f5f372341b63";
+  inputs.poetry2nixSrc = {
+    url = "github:nix-community/poetry2nix";
+    inputs.nixpkgs.follows = "nixpkgs";
+  };
 
-  outputs = { self, nixpkgs, flake-utils, poetry2nix }:
+  outputs = { self, nixpkgs, flake-utils, poetry2nixSrc }:
-    {
+    flake-utils.lib.eachDefaultSystem (system:
-      # Nixpkgs overlay providing the application
-      overlay = nixpkgs.lib.composeManyExtensions [
-        poetry2nix.overlay
-        (final: prev: {
-          # The application
-          deepdog = prev.poetry2nix.mkPoetryApplication {
-            overrides = final.poetry2nix.overrides.withDefaults (self: super: {
-              # …
-              # workaround https://github.com/nix-community/poetry2nix/issues/568
-              pdme = super.pdme.overridePythonAttrs (old: {
-                buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
-              });
-            });
-            projectDir = ./.;
-          };
-          deepdogEnv = prev.poetry2nix.mkPoetryEnv {
-            overrides = final.poetry2nix.overrides.withDefaults (self: super: {
-              # …
-              # workaround https://github.com/nix-community/poetry2nix/issues/568
-              pdme = super.pdme.overridePythonAttrs (old: {
-                buildInputs = old.buildInputs or [ ] ++ [ final.python39.pkgs.poetry-core ];
-              });
-            });
-            projectDir = ./.;
-          };
-        })
-      ];
-    } // (flake-utils.lib.eachDefaultSystem (system:
       let
-        pkgs = import nixpkgs {
+        pkgs = nixpkgs.legacyPackages.${system};
-          inherit system;
+	poetry2nix = poetry2nixSrc.lib.mkPoetry2Nix { inherit pkgs; };
-          overlays = [ self.overlay ];
+      in {
-        };
+        packages = {
-      in
+	  deepdogApp = poetry2nix.mkPoetryApplication {
-      {
+            projectDir = self;
-        apps = {
+	    python = pkgs.python39;
-          deepdog = pkgs.deepdog;
+	    preferWheels = true;
-        };
+	  };
-
+	  deepdogEnv = poetry2nix.mkPoetryEnv {
-        defaultApp = pkgs.deepdog;
+	    projectDir = self;
-        devShell = pkgs.mkShell {
+	    python = pkgs.python39;
-          buildInputs = [
+	    preferWheels = true;
-            pkgs.poetry
+	    overrides = poetry2nix.overrides.withDefaults (self: super: {
-            pkgs.deepdogEnv
+	    });
-            pkgs.deepdog
+	  };
-          ];
+	  default = self.packages.${system}.deepdogEnv;
-          shellHook = ''
+	};
-            export DO_NIX_CUSTOM=1
+	devShells.default = pkgs.mkShell {
-          '';
+	  inputsFrom = [ self.packages.${system}.deepdogEnv ];
-          packages = [ pkgs.nodejs-16_x ];
+	  buildInputs = [
-        };
+	    pkgs.poetry
-
+	    self.packages.${system}.deepdogEnv
-      }));
+	    self.packages.${system}.deepdogApp
+	    pkgs.just
+	  ];
+	  shellHook = ''
+	    export DO_NIX_CUSTOM=1
+	  '';
+	};
+      }
+    );
 }

justfile

@@ -0,0 +1,54 @@
+
+# execute default build
+default: build
+
+# builds the python module using poetry
+build:
+	echo "building..."
+	poetry build
+
+# print a message displaying whether nix is being used
+checknix:
+	#!/usr/bin/env bash
+	set -euxo pipefail
+	if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
+		echo "In an interactive nix env."
+	else
+		echo "Using poetry as runner, no nix detected."
+	fi
+
+# run all tests
+test: fmt
+	#!/usr/bin/env bash
+	set -euxo pipefail
+	
+	if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
+		echo "testing, using nix..."
+		flake8 deepdog tests
+		mypy deepdog
+		pytest
+	else
+		echo "testing..."
+		poetry run flake8 deepdog tests
+		poetry run mypy deepdog
+		poetry run pytest
+	fi
+
+# format code
+fmt:
+	#!/usr/bin/env bash
+	set -euxo pipefail
+	if [[ "${DO_NIX_CUSTOM:=0}" -eq 1 ]]; then
+	      black .
+	else
+		poetry run black .
+	fi
+	find deepdog -type f -name "*.py" -exec sed -i -e 's/    /\t/g' {} \;
+	find tests -type f -name "*.py" -exec sed -i -e 's/    /\t/g' {} \;
+
+# release the app, checking that our working tree is clean and ready for release
+release:
+	./scripts/release.sh
+
+htmlcov:
+	poetry run pytest --cov-report=html

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "deepdog"
-version = "0.7.8"
+version = "0.7.9"
 description = ""
 authors = ["Deepak Mallubhotla <dmallubhotla+github@gmail.com>"]