def test_progress_max_refresh() -> None:
"""Test max_refresh argment."""
time = 0.0
def get_time() -> float:
nonlocal time
try:
return time
finally:
time = time + 1.0
console = Console(color_system=None,
width=80,
legacy_windows=False,
force_terminal=True)
column = TextColumn("{task.description}")
column.max_refresh = 3
progress = Progress(
column,
get_time=get_time,
auto_refresh=False,
console=console,
)
console.begin_capture()
with progress:
task_id = progress.add_task("start")
for tick in range(6):
progress.update(task_id, description=f"tick {tick}")
progress.refresh()
result = console.end_capture()
print(repr(result))
assert (
result ==
"\x1b[?25l\r\x1b[2Kstart\r\x1b[2Kstart\r\x1b[2Ktick 1\r\x1b[2Ktick 1\r\x1b[2Ktick 3\r\x1b[2Ktick 3\r\x1b[2Ktick 5\r\x1b[2Ktick 5\n\x1b[?25h"
)
class DefaultProgressHandler(BaseProgressHandler):
def __init__(self):
self.progress = Progress(
TextColumn("[bold blue]{task.fields[title]}", justify="right"),
BarColumn(bar_width=None),
"[progress.percentage]{task.percentage:>3.1f}%",
"•",
DownloadColumn(),
"•",
TransferSpeedColumn(),
"•",
TimeRemainingColumn(),
)
def initialize(self, *args, **kwargs):
super().initialize(*args)
self.download_task = self.progress.add_task(self.track_title,
title=self.track_title,
total=self.total_size)
self.progress.start()
def update(self, *args, **kwargs):
super().update(**kwargs)
self.progress.update(self.download_task,
advance=self.current_chunk_size)
def close(self, *args, **kwargs):
self.progress.stop()
class ProgressBar:
OPTIONS = [
"[progress.description]{task.description}",
BarColumn(),
"[progress.percentage]{task.completed:>6}/{task.total}",
TimeElapsedColumn(),
]
def __init__(self, description, total):
self.description = description
self.total = total
def __enter__(self):
self.progress = Progress(*self.OPTIONS)
self.progress.start()
self.task = self.progress.add_task(self.description, total=self.total)
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.progress.stop()
def print(self, message):
self.progress.console.print(message)
def advance(self, advance=1):
self.progress.update(self.task, advance=advance)
def predict(trainData, trainLabel, testData, K=27):
'''
测试模型正确率
===========
Arguments
---------
- `trainData` 训练集数据集
- `trainLabel` 训练集标记
- `testData` 测试集数据集
- `K` 选择近邻数
Returns
-------
- `predictLabel` 预测标签
'''
predictLabel = []
progress = Progress(
"[progress.description]{task.description}",
BarColumn(bar_width=None),
"[progress.percentage]{task.completed}/{task.total}",
"•",
TimeRemainingColumn(),
) # rich 进度条
progress.start()
testTask = progress.add_task("[cyan]predicting...", total=len(testData))
for x in testData:
predictLabel.append(NearestNeighbor(trainData, trainLabel, x,
K)) # 预测标签分类
progress.update(testTask, advance=1)
progress.stop()
return predictLabel
def download(self, batch, articles, folder):
"""
Download a pdf batch
"""
log_file = os.path.join(folder, 'missing.log')
logger.remove()
logger.add(log_file,
format="{time} {level} {message}",
mode='w',
level="INFO")
assert len(articles) > 0, 'no article.'
progress = Progress(TextColumn(
"[progress.description]{task.description}",
table_column=Column(ratio=1)),
TimeElapsedColumn(table_column=Column(ratio=1)),
BarColumn(table_column=Column(ratio=2)),
"| {task.completed} of {task.total:>2.0f}",
expand=False)
missing = 0
with progress:
task = progress.add_task(f" {batch} |", total=len(articles))
for article in articles:
done = self.get_article(
article['article_url'],
os.path.join(folder, article['file_name']))
if done:
progress.update(task, advance=1)
else:
missing += 1
logger.info("NOT_FOUND_IN_SCI-HUB | " +
article['warning_str'])
return missing, log_file
class _Progress:
def __init__(self, show_limit: int = 50):
from rich.progress import Progress, BarColumn, TimeRemainingColumn
self._progress = Progress(
"[progress.description]{task.description}",
BarColumn(style="bar.back",
complete_style="bar.complete",
finished_style="bar.complete"),
"[progress.percentage]{task.percentage:>3.0f}%",
TimeRemainingColumn(),
auto_refresh=False)
self._last_update = _datetime.now()
self._show_limit = show_limit
self._completed = {}
self._have_entered = False
self._enter_args = None
def __enter__(self, *args, **kwargs):
self._enter_args = (args, kwargs)
return self
def __exit__(self, *args, **kwargs):
if self._have_entered:
self._progress.__exit__(*args, **kwargs)
return False
def add_task(self, description: str, total: int):
if total > self._show_limit:
if not self._have_entered:
args, kwargs = self._enter_args
self._progress.__enter__(*args, **kwargs)
self._have_entered = True
task_id = self._progress.add_task(description=description,
total=total)
self._completed[task_id] = 0
return task_id
else:
return None
def update(self, task_id: int, completed: float = None,
advance: float = None, force_update: bool = False):
if task_id is None:
return
elif completed is not None:
self._completed[task_id] = completed
elif advance is not None:
self._completed[task_id] += advance
else:
return
now = _datetime.now()
if force_update or (now - self._last_update).total_seconds() > 0.1:
self._progress.update(task_id=task_id,
completed=self._completed[task_id])
self._progress.refresh()
self._last_update = now
async def fetch_taxid_call(name: str, progress: Progress,
q: asyncio.queues.Queue, task: int):
"""
Handles calling asynchronous taxon id retrievals and updating task progress.
Puts results in a asyncio Queue.
Parameters:
name (str): name of a OTU
progress (Progress): Progress object for current tasks that can be updated
q (asyncio.queues.Queue): Queue containing current results of tasks
task (int): ID for a given progress task
"""
taxid = await asyncio.get_event_loop().run_in_executor(
None, fetch_taxid, name)
if taxid is None:
description = f"[red]Could not retrieve taxon ID for {name}"
result = f"[red]:x: Not found"
else:
description = f"[green]Retrieved taxon ID for {name}"
result = f"[green]:heavy_check_mark: {taxid}"
progress.print(description, result)
progress.update(task, advance=1)
await q.put((name, taxid))
def make_progress() -> Progress:
_time = 0.0
def fake_time():
nonlocal _time
try:
return _time
finally:
_time += 1
console = Console(
file=io.StringIO(),
force_terminal=True,
color_system="truecolor",
width=80,
legacy_windows=False,
)
progress = Progress(console=console, get_time=fake_time, auto_refresh=False)
task1 = progress.add_task("foo")
task2 = progress.add_task("bar", total=30)
progress.advance(task2, 16)
task3 = progress.add_task("baz", visible=False)
task4 = progress.add_task("egg")
progress.remove_task(task4)
task4 = progress.add_task("foo2", completed=50, start=False)
progress.stop_task(task4)
progress.start_task(task4)
progress.update(
task4, total=200, advance=50, completed=200, visible=True, refresh=True
)
progress.stop_task(task4)
return progress
class ProgressBarCallback(tf.keras.callbacks.Callback):
def __init__(self, steps: int):
super().__init__()
self.steps = steps
self.task = None
self.bar = Progress(
TextColumn(
"Iteration {task.fields[iteration]}/{task.fields[cumul]}"),
BarColumn(),
TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
TextColumn("Loss = {task.fields[loss]:.5f} | ⏳ "),
TimeRemainingColumn(),
TextColumn("lr = {task.fields[lr]:.6f}"),
)
def on_train_begin(self, logs=None):
self.task = self.task = self.bar.add_task(
description="Optimizing...",
total=self.steps,
iteration=self.model._tot_batches,
loss=self.model._loss,
cumul=self.steps + self.model._tot_batches,
lr=float(tf.keras.backend.get_value(self.model.optimizer.lr)))
def on_train_batch_end(self, batch, logs=None):
self.model._tot_batches += 1
self.bar.update(
self.task,
advance=1,
refresh=True,
iteration=self.model._tot_batches,
loss=self.model._loss,
lr=float(tf.keras.backend.get_value(self.model.optimizer.lr)))
def train(self, input_path, train_datasets):
"""
Train the model
:param num_steps:
:return:
"""
# Define the optimizer
optimizer = tf.keras.optimizers.Adam(learning_rate=self.learning_rate)
# Build model graph
self.build_model(input_path=input_path,
train_datasets=train_datasets,
mode="train")
# Training loop
progress_bar = Progress(
"[bold blue]{task.description}",
"[bold cyan]Step: {task.fields[step]}, Loss: {task.fields[loss]}",
BarColumn(bar_width=None),
)
training_progress = progress_bar.add_task(self.model_name,
total=self.num_steps,
step=0,
loss=1)
with progress_bar:
for step in range(self.num_steps):
x, y = self.data_iter.get_next()
with tf.GradientTape() as tape:
self.logits = self.model(x, training=True)
loss = self.compute_loss(self.logits, y)
grads = tape.gradient(loss, self.model.trainable_weights)
optimizer.apply_gradients(
zip(grads, self.model.trainable_weights))
progress_bar.update(training_progress,
advance=1,
step=step,
loss=f"{loss:.4f}")
# Collect garbage after 100 steps - otherwise runs out of memory
if step % 100 == 0:
gc.collect()
# Save the trained model
self.model.save(self.model_dir)
pd.DataFrame(self.labels).to_csv(os.path.join(self.model_dir,
"celltypes.txt"),
sep="\t")
pd.DataFrame(self.sig_genes).to_csv(os.path.join(
self.model_dir, "genes.txt"),
sep="\t")
class ProgressHandler(BaseProgressHandler):
def __init__(self):
self.tracks = {}
self.progress = Progress(
TextColumn("[bold blue]{task.fields[title]}", justify="left"),
BarColumn(bar_width=None),
"[progress.percentage]{task.percentage:>3.2f}%",
"•",
DownloadColumn(),
"•",
TransferSpeedColumn(),
"•",
TimeRemainingColumn(),
transient=True)
def initialize(self, iterable, track_title, track_quality, total_size,
chunk_size, **kwargs):
track_id = kwargs["track_id"]
task = self.progress.add_task(track_title,
title=track_title,
total=total_size)
self.progress.console.print(
f"[bold red]{track_title}[/] has started downloading.")
self.tracks[track_id] = {
"id": track_id,
"iterable": iterable,
"title": track_title,
"quality": track_quality,
"total_size": total_size,
"chunk_size": chunk_size,
"task": task,
"size_downloaded": 0,
"current_chunk_size": 0
}
self.progress.start()
def update(self, *args, **kwargs):
track = self.tracks[kwargs["track_id"]]
track["current_chunk_size"] = kwargs["current_chunk_size"]
track["size_downloaded"] += track["current_chunk_size"]
self.progress.update(track["task"],
advance=track["current_chunk_size"])
def close(self, *args, **kwargs):
track = self.tracks[kwargs["track_id"]]
track_title = track["title"]
self.progress.print(
f"[bold red]{track_title}[/] is done downloading.")
def close_progress(self):
self.progress.refresh()
self.progress.stop()
async def add_progress_bar(self, progress_task: ProgressTask,
progress: Progress) -> None:
"""creates a new progress task and adds a ProgressTask instance to the internal registry"""
task_id = progress.add_task(**progress_task.kwargs)
if progress_task.progress:
progress.update(task_id, advance=progress_task.progress)
task = [t for t in progress.tasks if t.id == task_id][0]
progress_task.task = task
self.tasks[int(progress_task.sim_id)] = progress_task
def update(progress: Progress, overall: int, items: dict[str, tuple[int, str]], stats: dict[str, Any]) -> None:
progress.update(
overall,
description=f"{stats['complete']} Gifts Obtained",
completed=stats["progress"],
)
for item in stats["items"]:
progress.update(
items[item[1]],
completed=item[0],
)
class Log():
def __init__(self):
self.__progress = Progress(
SpinnerColumn(),
TextColumn(
"[progress.description]{task.description} {task.fields[current]}"
),
"•",
BarColumn(),
"•",
TransferSpeedColumn(),
TimeRemainingColumn(),
console=Console(),
transient=True,
expand=True)
self.__console = self.__progress.console
def success(self, msg: str, **kwargs):
self.__console.print(f"[bold green]{msg}[/bold green]", **kwargs)
def error(self, msg: str, **kwargs):
self.__console.print(f"[bold red]{msg}[/bold red]", **kwargs)
def warning(self, msg: str, **kwargs):
self.__console.print(f"[bold yellow]{msg}[/bold yellow]", **kwargs)
# Get all the details avaiable about one or more object passed to it
def details(self, *args):
for arg in args:
inspect(arg, methods=True)
# This a simple and quick variadic print with option for some styling
def debug(self, *args, **kwargs):
for arg in args:
self.__console.print(arg, **kwargs)
# Print documentation both in a single string or markdown format
def documentation(self, title: str, doc: str, markdown: bool = False):
self.__console.rule(f"[bold yellow]{title}", align="center")
if markdown:
md = Markdown(doc)
self.__console.print(md, justify="center")
else:
self.__console.print(f"[bold yellow]{doc}", justify="left")
# Construct and return a tuple with ...
def progress_bar_builder(self, label: str, total: int, current: str = ""):
task_id = self.__progress.add_task(label, total, current=current)
def update_task(increment: int, current: str):
self.__progress.update(task_id, current=current, advance=increment)
return (self.__progress, update_task)
async def download_image(session: aiohttp.ClientSession, url: str,
file_path: str, progress: Progress, task):
try:
async with session.get(url) as response:
assert response.status == 200
async with aiofiles.open(file_path, 'wb') as f:
await f.write(await response.read())
progress.console.print(f'Downloaded {url} to {file_path}')
except Exception as e:
progress.console.print(f'Download for {url} failed: {str(e)}')
progress.update(task, advance=1)
def benchmark(name: str, func: Callable, num_repeats: int,
progress_bar: Progress) -> List[float]:
"""Return list of run times for func, num_repeats times"""
run_times = []
text_color = '[blue]'
task = progress_bar.add_task(f"{text_color}{name}", total=num_repeats)
for i in range(num_repeats):
progress_bar.tasks[
task].description = f"{text_color}{name}: run {i + 1}/{num_repeats}"
run_times.append(timeit(func, number=1))
progress_bar.update(task, advance=1)
return run_times
async def download_image(
progress: Progress, task_id: TaskID, image_url: str, destination: Path
) -> None:
async with httpx.AsyncClient() as client:
response = await client.get(image_url)
if response.status_code >= 400:
progress.console.print(f'image [blue]{image_url}[/] could not be downloaded')
progress.update(task_id, advance=1)
return
path = destination / image_url.split('/')[-1]
path.write_bytes(response.content)
progress.update(task_id, advance=1)
def generate_progress(
self, progress: Progress,
task: TaskID) -> Union[ConsoleRenderable, RichCast, str]:
"""Returns the updated progress bar"""
total = 0
completed = 0
for w in self.workers:
if w.__meta__.name == "CSVReader":
total += w.__meta__.items_processed
elif w.__meta__.name == "DomainResolver":
completed += w.__meta__.items_processed
progress.update(task, total=total, completed=completed)
return progress.get_renderable()
def track(self, tasks, label="Processing"):
progress = Progress(
"[progress.description][yellow]{task.description} {task.fields[key]}",
BarColumn(),
"[progress.percentage]{task.percentage:>3.0f}%",
TimeRemainingColumn(),
console=self)
with progress:
task_bar = progress.add_task(label, total=len(tasks), key="")
for idx, task in enumerate(tasks):
progress.update(task_bar, completed=idx, key=task)
yield task
progress.update(task_bar, advance=1, key="finished")
class ProgressManager():
progress = None
task = None
current_pos = 0
total = 0
def __init__(self, total, current_pos):
self.total = total
self.progress = Progress(
#SpinnerColumn(),
"{task.description}",
BarColumn(),
"{task.completed}",
"of",
"{task.total}",
"documents.",
)
self.task = self.progress.add_task("Progress:", total=self.total)
# Current position adjusted to non-zero
self.current_pos = current_pos + 1
print('Document %s of %s' % (self.current_pos, self.total))
# First document
self.add_progress(self.current_pos)
def __rich__(self) -> Panel:
try:
return Panel(self.progress)
except Exception as e:
print(e)
def add_progress(self, advance):
self.progress.update(self.task, advance=advance)
def next(self):
if self.current_pos == self.total:
self.current_pos = 1
self.progress.update(self.task, advance=-self.total + 1)
else:
self.progress.update(self.task, advance=1)
self.current_pos += 1
def prev(self):
if self.current_pos == 1:
self.current_pos = self.total
self.progress.update(self.task, advance=self.total - 1)
else:
self.progress.update(self.task, advance=-1)
self.current_pos -= 1
def predict(trainData,
trainLabel,
testData,
kernel='Gaussian',
C=200,
epsilon=0.0001,
sigma=10,
p=2):
'''
测试模型正确率
===========
Arguments
---------
- `trainData` 训练集数据集
- `trainLabel` 训练集标记
- `testData` 测试集数据集
- `kernel` 核函数
- `C` 软间隔惩罚参数
- `epsilon` 松弛变量
- `sigma` 高斯核函数参数
- `p` 多项式核参数
Returns
-------
- `predictLabel` 预测标签
'''
predictLabel = []
machine = SupportVectorMachine(kernel=kernel,
C=C,
epsilon=epsilon,
sigma=sigma)
machine.train(trainData, trainLabel)
progress = Progress(
"[progress.description]{task.description}",
BarColumn(bar_width=None),
"[progress.percentage]{task.completed}/{task.total}",
"•",
TimeRemainingColumn(),
) # rich 进度条
progress.start()
testTask = progress.add_task("[cyan]predicting...", total=len(testData))
for testDatum in testData:
predictLabel.append(machine.classify(testDatum)) # 预测标签分类
progress.update(testTask, advance=1)
progress.stop()
return predictLabel
async def advance_progress(self, data: Dict, progress: Progress) -> None:
"""advances the progress bar for the given tasks by the current simulation progress"""
simulation_id = data["data"]["simulation_id"]
sim_progress = data["data"]["progress"]
progress_task = self.tasks.get(int(simulation_id))
if not progress_task.task.started:
progress.start_task(progress_task.task.id)
# progress.console.print(f">>>>>>>>>> {sim_progress}")
if int(sim_progress) <= progress_task.task.percentage:
return
advance_by = int(sim_progress) - int(progress_task.task.percentage)
progress.update(progress_task.task.id, advance=advance_by)
# auto_refresh is False so do this manually
progress.refresh()
def _download(url: str, root: str):
os.makedirs(root, exist_ok=True)
filename = os.path.basename(url)
download_target = os.path.join(root, filename)
if os.path.isfile(download_target):
return download_target
if os.path.exists(download_target) and not os.path.isfile(download_target):
raise FileExistsError(f'{download_target} exists and is not a regular file')
from rich.progress import (
DownloadColumn,
Progress,
TextColumn,
TimeRemainingColumn,
TransferSpeedColumn,
)
progress = Progress(
TextColumn("[bold blue]{task.fields[filename]}", justify="right"),
"[progress.percentage]{task.percentage:>3.1f}%",
"•",
DownloadColumn(),
"•",
TransferSpeedColumn(),
"•",
TimeRemainingColumn(),
)
with progress:
task = progress.add_task('download', filename=url, start=False)
with urllib.request.urlopen(url) as source, open(
download_target, 'wb'
) as output:
progress.update(task, total=int(source.info().get('Content-Length')))
progress.start_task(task)
while True:
buffer = source.read(8192)
if not buffer:
break
output.write(buffer)
progress.update(task, advance=len(buffer))
return download_target
def create_subsample_dataset(self, x, y, celltypes):
"""
Generate many artifial bulk samples with known fractions
This function will create normal and sparse samples (no_samples)
@param x:
@param y:
@param celltypes:
@return:
"""
sim_x = []
sim_y = []
# Create normal samples
progress_bar = Progress(
"[bold blue]{task.description}",
"[bold cyan]{task.fields[samples]}",
BarColumn(bar_width=None),
)
with progress_bar:
normal_samples_progress = progress_bar.add_task(
"Normal samples", total=self.num_samples, samples=0)
sparse_samples_progress = progress_bar.add_task(
"Sparse samples", total=self.num_samples, samples=0)
# Create normal samples
for i in range(self.num_samples):
progress_bar.update(normal_samples_progress,
advance=1,
samples=i + 1)
sample, label = self.create_subsample(x, y, celltypes)
sim_x.append(sample)
sim_y.append(label)
# Create sparase samples
for i in range(self.num_samples):
progress_bar.update(sparse_samples_progress,
advance=1,
samples=i + 1)
sample, label = self.create_subsample(x,
y,
celltypes,
sparse=True)
sim_x.append(sample)
sim_y.append(label)
sim_x = pd.concat(sim_x, axis=1).T
sim_y = pd.DataFrame(sim_y, columns=celltypes)
return sim_x, sim_y
def run(self, manager: "pwncat.manager.Manager", args):
# Create a progress bar for the download
progress = Progress(
TextColumn("[bold cyan]{task.fields[filename]}", justify="right"),
BarColumn(bar_width=None),
"[progress.percentage]{task.percentage:>3.1f}%",
"•",
DownloadColumn(),
"•",
TransferSpeedColumn(),
"•",
TimeRemainingColumn(),
)
if not args.destination:
args.destination = f"./{os.path.basename(args.source)}"
try:
length = os.path.getsize(args.source)
started = time.time()
with progress:
task_id = progress.add_task("upload",
filename=args.destination,
total=length,
start=False)
with open(args.source, "rb") as source:
with manager.target.platform.open(args.destination,
"wb") as destination:
progress.start_task(task_id)
copyfileobj(
source,
destination,
lambda count: progress.update(task_id,
advance=count),
)
progress.update(task_id,
filename="draining buffers...")
progress.stop_task(task_id)
progress.start_task(task_id)
progress.update(task_id, filename=args.destination)
elapsed = time.time() - started
console.log(f"uploaded [cyan]{human_readable_size(length)}[/cyan] "
f"in [green]{human_readable_delta(elapsed)}[/green]")
except (FileNotFoundError, PermissionError, IsADirectoryError) as exc:
self.parser.error(str(exc))
def make_progress() -> Progress:
console = Console(file=io.StringIO(), force_terminal=True)
progress = Progress(console=console)
task1 = progress.add_task("foo")
task2 = progress.add_task("bar", 30)
progress.advance(task2, 16)
task3 = progress.add_task("baz", visible=False)
task4 = progress.add_task("egg")
progress.remove_task(task4)
task4 = progress.add_task("foo2", completed=50, start=False)
progress.start_task(task4)
progress.update(
task4, total=200, advance=50, completed=200, visible=True, refresh=True
)
return progress
def parse_apk(apkfile, workers, fn_match=None, outfile=None):
console = Console()
console.log(f"Parsing {apkfile} with {workers} workers ...")
dexes = list(extract_dex_files(apkfile))
console.log(f"Found {len(dexes)} DEX file.")
total = sum(map(lambda d: len(d.data), dexes))
progress = Progress(
TextColumn("[progress.description]{task.description}"),
BarColumn(
complete_style='bar.complete',
finished_style='bar.finished',
pulse_style='bar.pulse',
),
TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
TimeRemainingColumn(),
TimeElapsedColumn(),
console=console,
)
out = {}
out.update(JNI_COMMON)
num_classes = 0
t0 = datetime.now()
with progress:
task = progress.add_task("Analyzing...", total=total)
with multiprocessing.Pool(workers) as pool:
result = pool.imap(parse_dex_proc, dexes)
for dex, count, res in result:
if count == 0:
console.log(
"Parse {} ({} bytes) [bold red]failed: {}".format(
dex.name, len(dex.data), res))
continue
console.log("Parse {} ({} bytes), found {} classes.".format(
dex.name, len(dex.data), count))
num_classes += count
progress.update(task, advance=len(dex.data))
for cname, data in res.items():
if fn_match and not fn_match(cname):
continue
out.update(data)
console.log("Aanlyzed {} classes, cost: {}".format(num_classes,
datetime.now() - t0))
console.log("Found {} JNI methods.".format(len(out)))
if not outfile:
console.print_json(data=out)
else:
with open(outfile, 'w') as f:
json.dump(out, f, indent=2, ensure_ascii=False)
def progress_step(self, step_key, step_name, total):
"""Context manager to show a progress bar during a step execution."""
step_progress = Progress(
'{task.description}',
SpinnerColumn(spinner_name='earth'),
BarColumn(),
TextColumn('[progress.percentage]{task.percentage:>3.0f}%'),
)
step_job = step_progress.add_task(step_name, total=total)
self.progress_bars[step_key] = {
C.PROGRESS_KEY: step_progress,
C.JOB_KEY: step_job,
}
self.progress_table.add_row(step_progress)
yield
step_progress.update(step_job, completed=step_progress.tasks[0].total)
def retrieve_over_http(url, output_file_path):
"""Download file from remote location, with progress bar.
Parameters
----------
url : str
Remote URL.
output_file_path : str or Path
Full file destination for download.
"""
# Make Rich progress bar
progress = Progress(
TextColumn("[bold]Downloading...", justify="right"),
BarColumn(bar_width=None),
"{task.percentage:>3.1f}%",
"•",
DownloadColumn(),
"• speed:",
TransferSpeedColumn(),
"• ETA:",
TimeRemainingColumn(),
)
CHUNK_SIZE = 4096
response = requests.get(url, stream=True)
try:
with progress:
task_id = progress.add_task(
"download",
filename=output_file_path.name,
start=True,
total=int(response.headers.get("content-length", 0)),
)
with open(output_file_path, "wb") as fout:
for chunk in response.iter_content(chunk_size=CHUNK_SIZE):
fout.write(chunk)
progress.update(task_id, advance=len(chunk), refresh=True)
except requests.exceptions.ConnectionError:
output_file_path.unlink()
raise requests.exceptions.ConnectionError(
f"Could not download file from {url}"
)
class RichLogger(Logger):
def __init__(self) -> None:
self.console = autogoal.logging.console()
self.logger = autogoal.logging.logger()
def begin(self, generations, pop_size):
self.progress = Progress(console=self.console)
self.pop_counter = self.progress.add_task("Generation", total=pop_size)
self.total_counter = self.progress.add_task("Overall",
total=pop_size *
generations)
self.progress.start()
self.console.rule("Search starting", style="blue")
def sample_solution(self, solution):
self.progress.advance(self.pop_counter)
self.progress.advance(self.total_counter)
self.console.rule("Evaluating pipeline")
self.console.print(repr(solution))
def eval_solution(self, solution, fitness):
self.console.print(Panel(f"📈 Fitness=[blue]{fitness:.3f}"))
def error(self, e: Exception, solution):
self.console.print(f"⚠️[red bold]Error:[/] {e}")
def start_generation(self, generations, best_fn):
self.console.rule(
f"New generation - Remaining={generations} - Best={best_fn or 0:.3f}"
)
def start_generation(self, generations, best_fn):
self.progress.update(self.pop_counter, completed=0)
def update_best(self, new_best, new_fn, previous_best, previous_fn):
self.console.print(
Panel(
f"🔥 Best improved from [red bold]{previous_fn or 0:.3f}[/] to [green bold]{new_fn:.3f}[/]"
))
def end(self, best, best_fn):
self.console.rule(f"Search finished")
self.console.print(repr(best))
self.console.print(Panel(f"🌟 Best=[green bold]{best_fn or 0:.3f}"))
self.progress.stop()
self.console.rule("Search finished", style="red")
