Merge branch 'feature/project-cli' into develop

This commit is contained in:
Ines Montani 2020-06-29 10:49:05 +02:00
commit bac8a8d766
8 changed files with 811 additions and 49 deletions

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@ -15,6 +15,7 @@ from .evaluate import evaluate # noqa: F401
from .convert import convert # noqa: F401
from .init_model import init_model # noqa: F401
from .validate import validate # noqa: F401
from .project import project_clone, project_assets, project_run # noqa: F401
@app.command("link", no_args_is_help=True, deprecated=True, hidden=True)

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@ -1,4 +1,3 @@
from typing import Optional
import typer
from typer.main import get_command

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@ -1,7 +1,9 @@
from typing import Optional, List
from typing import Optional, List, Dict
from timeit import default_timer as timer
from wasabi import Printer
from pathlib import Path
import re
import srsly
from ..gold import Corpus
from ..tokens import Doc
@ -16,13 +18,12 @@ def evaluate_cli(
# fmt: off
model: str = Arg(..., help="Model name or path"),
data_path: Path = Arg(..., help="Location of JSON-formatted evaluation data", exists=True),
output: Optional[Path] = Opt(None, "--output", "-o", help="Output JSON file for metrics", dir_okay=False),
gpu_id: int = Opt(-1, "--gpu-id", "-g", help="Use GPU"),
gold_preproc: bool = Opt(False, "--gold-preproc", "-G", help="Use gold preprocessing"),
displacy_path: Optional[Path] = Opt(None, "--displacy-path", "-dp", help="Directory to output rendered parses as HTML", exists=True, file_okay=False),
displacy_limit: int = Opt(25, "--displacy-limit", "-dl", help="Limit of parses to render as HTML"),
return_scores: bool = Opt(False, "--return-scores", "-R", help="Return dict containing model scores"),
# fmt: on
# fmt: on
):
"""
Evaluate a model. To render a sample of parses in a HTML file, set an
@ -31,24 +32,24 @@ def evaluate_cli(
evaluate(
model,
data_path,
output=output,
gpu_id=gpu_id,
gold_preproc=gold_preproc,
displacy_path=displacy_path,
displacy_limit=displacy_limit,
silent=False,
return_scores=return_scores,
)
def evaluate(
model: str,
data_path: Path,
output: Optional[Path],
gpu_id: int = -1,
gold_preproc: bool = False,
displacy_path: Optional[Path] = None,
displacy_limit: int = 25,
silent: bool = True,
return_scores: bool = False,
) -> Scorer:
msg = Printer(no_print=silent, pretty=not silent)
util.fix_random_seed()
@ -56,21 +57,19 @@ def evaluate(
util.use_gpu(gpu_id)
util.set_env_log(False)
data_path = util.ensure_path(data_path)
output_path = util.ensure_path(output)
displacy_path = util.ensure_path(displacy_path)
if not data_path.exists():
msg.fail("Evaluation data not found", data_path, exits=1)
if displacy_path and not displacy_path.exists():
msg.fail("Visualization output directory not found", displacy_path, exits=1)
corpus = Corpus(data_path, data_path)
if model.startswith("blank:"):
nlp = util.get_lang_class(model.replace("blank:", ""))()
else:
nlp = util.load_model(model)
nlp = util.load_model(model)
dev_dataset = list(corpus.dev_dataset(nlp, gold_preproc=gold_preproc))
begin = timer()
scorer = nlp.evaluate(dev_dataset, verbose=False)
end = timer()
nwords = sum(len(ex.doc) for ex in dev_dataset)
nwords = sum(len(ex.predicted) for ex in dev_dataset)
results = {
"Time": f"{end - begin:.2f} s",
"Words": nwords,
@ -90,10 +89,22 @@ def evaluate(
"Sent R": f"{scorer.sent_r:.2f}",
"Sent F": f"{scorer.sent_f:.2f}",
}
data = {re.sub(r"[\s/]", "_", k.lower()): v for k, v in results.items()}
msg.table(results, title="Results")
if scorer.ents_per_type:
data["ents_per_type"] = scorer.ents_per_type
print_ents_per_type(msg, scorer.ents_per_type)
if scorer.textcats_f_per_cat:
data["textcats_f_per_cat"] = scorer.textcats_f_per_cat
print_textcats_f_per_cat(msg, scorer.textcats_f_per_cat)
if scorer.textcats_auc_per_cat:
data["textcats_auc_per_cat"] = scorer.textcats_auc_per_cat
print_textcats_auc_per_cat(msg, scorer.textcats_auc_per_cat)
if displacy_path:
docs = [ex.doc for ex in dev_dataset]
docs = [ex.predicted for ex in dev_dataset]
render_deps = "parser" in nlp.meta.get("pipeline", [])
render_ents = "ner" in nlp.meta.get("pipeline", [])
render_parses(
@ -105,8 +116,11 @@ def evaluate(
ents=render_ents,
)
msg.good(f"Generated {displacy_limit} parses as HTML", displacy_path)
if return_scores:
return scorer.scores
if output_path is not None:
srsly.write_json(output_path, data)
msg.good(f"Saved results to {output_path}")
return data
def render_parses(
@ -128,3 +142,40 @@ def render_parses(
)
with (output_path / "parses.html").open("w", encoding="utf8") as file_:
file_.write(html)
def print_ents_per_type(msg: Printer, scores: Dict[str, Dict[str, float]]) -> None:
data = [
(k, f"{v['p']:.2f}", f"{v['r']:.2f}", f"{v['f']:.2f}")
for k, v in scores.items()
]
msg.table(
data,
header=("", "P", "R", "F"),
aligns=("l", "r", "r", "r"),
title="NER (per type)",
)
def print_textcats_f_per_cat(msg: Printer, scores: Dict[str, Dict[str, float]]) -> None:
data = [
(k, f"{v['p']:.2f}", f"{v['r']:.2f}", f"{v['f']:.2f}")
for k, v in scores.items()
]
msg.table(
data,
header=("", "P", "R", "F"),
aligns=("l", "r", "r", "r"),
title="Textcat F (per type)",
)
def print_textcats_auc_per_cat(
msg: Printer, scores: Dict[str, Dict[str, float]]
) -> None:
msg.table(
[(k, f"{v['roc_auc_score']:.2f}") for k, v in scores.items()],
header=("", "ROC AUC"),
aligns=("l", "r"),
title="Textcat ROC AUC (per label)",
)

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@ -16,8 +16,9 @@ def package_cli(
# fmt: off
input_dir: Path = Arg(..., help="Directory with model data", exists=True, file_okay=False),
output_dir: Path = Arg(..., help="Output parent directory", exists=True, file_okay=False),
meta_path: Optional[Path] = Opt(None, "--meta-path", "-m", help="Path to meta.json", exists=True, dir_okay=False),
meta_path: Optional[Path] = Opt(None, "--meta-path", "--meta", "-m", help="Path to meta.json", exists=True, dir_okay=False),
create_meta: bool = Opt(False, "--create-meta", "-c", "-C", help="Create meta.json, even if one exists"),
version: Optional[str] = Opt(None, "--version", "-v", help="Package version to override meta"),
force: bool = Opt(False, "--force", "-f", "-F", help="Force overwriting existing model in output directory"),
# fmt: on
):
@ -32,6 +33,7 @@ def package_cli(
input_dir,
output_dir,
meta_path=meta_path,
version=version,
create_meta=create_meta,
force=force,
silent=False,
@ -42,6 +44,7 @@ def package(
input_dir: Path,
output_dir: Path,
meta_path: Optional[Path] = None,
version: Optional[str] = None,
create_meta: bool = False,
force: bool = False,
silent: bool = True,
@ -61,10 +64,13 @@ def package(
if not meta_path.exists() or not meta_path.is_file():
msg.fail("Can't load model meta.json", meta_path, exits=1)
meta = srsly.read_json(meta_path)
meta = get_meta(input_dir, meta)
if version is not None:
meta["version"] = version
if not create_meta: # only print if user doesn't want to overwrite
msg.good("Loaded meta.json from file", meta_path)
else:
meta = generate_meta(input_dir, meta, msg)
meta = generate_meta(meta, msg)
errors = validate(ModelMetaSchema, meta)
if errors:
msg.fail("Invalid model meta.json", "\n".join(errors), exits=1)
@ -101,20 +107,20 @@ def create_file(file_path: Path, contents: str) -> None:
file_path.open("w", encoding="utf-8").write(contents)
def generate_meta(
model_path: Union[str, Path], existing_meta: Dict[str, Any], msg: Printer
def get_meta(
model_path: Union[str, Path], existing_meta: Dict[str, Any]
) -> Dict[str, Any]:
meta = existing_meta or {}
settings = [
("lang", "Model language", meta.get("lang", "en")),
("name", "Model name", meta.get("name", "model")),
("version", "Model version", meta.get("version", "0.0.0")),
("description", "Model description", meta.get("description", False)),
("author", "Author", meta.get("author", False)),
("email", "Author email", meta.get("email", False)),
("url", "Author website", meta.get("url", False)),
("license", "License", meta.get("license", "MIT")),
]
meta = {
"lang": "en",
"name": "model",
"version": "0.0.0",
"description": None,
"author": None,
"email": None,
"url": None,
"license": "MIT",
}
meta.update(existing_meta)
nlp = util.load_model_from_path(Path(model_path))
meta["spacy_version"] = util.get_model_version_range(about.__version__)
meta["pipeline"] = nlp.pipe_names
@ -124,6 +130,23 @@ def generate_meta(
"keys": nlp.vocab.vectors.n_keys,
"name": nlp.vocab.vectors.name,
}
if about.__title__ != "spacy":
meta["parent_package"] = about.__title__
return meta
def generate_meta(existing_meta: Dict[str, Any], msg: Printer) -> Dict[str, Any]:
meta = existing_meta or {}
settings = [
("lang", "Model language", meta.get("lang", "en")),
("name", "Model name", meta.get("name", "model")),
("version", "Model version", meta.get("version", "0.0.0")),
("description", "Model description", meta.get("description", None)),
("author", "Author", meta.get("author", None)),
("email", "Author email", meta.get("email", None)),
("url", "Author website", meta.get("url", None)),
("license", "License", meta.get("license", "MIT")),
]
msg.divider("Generating meta.json")
msg.text(
"Enter the package settings for your model. The following information "
@ -132,8 +155,6 @@ def generate_meta(
for setting, desc, default in settings:
response = get_raw_input(desc, default)
meta[setting] = default if response == "" and default else response
if about.__title__ != "spacy":
meta["parent_package"] = about.__title__
return meta
@ -184,12 +205,12 @@ def setup_package():
setup(
name=model_name,
description=meta['description'],
author=meta['author'],
author_email=meta['email'],
url=meta['url'],
description=meta.get('description'),
author=meta.get('author'),
author_email=meta.get('email'),
url=meta.get('url'),
version=meta['version'],
license=meta['license'],
license=meta.get('license'),
packages=[model_name],
package_data={model_name: list_files(model_dir)},
install_requires=list_requirements(meta),

657
spacy/cli/project.py Normal file
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@ -0,0 +1,657 @@
from typing import List, Dict, Any, Optional
import typer
import srsly
from pathlib import Path
from wasabi import msg
import subprocess
import shlex
import os
import re
import shutil
import sys
import requests
import tqdm
from ._app import app, Arg, Opt, COMMAND, NAME
from .. import about
from ..schemas import ProjectConfigSchema, validate
from ..util import ensure_path, run_command, make_tempdir, working_dir
from ..util import get_hash, get_checksum
CONFIG_FILE = "project.yml"
DVC_CONFIG = "dvc.yaml"
DIRS = [
"assets",
"metas",
"configs",
"packages",
"metrics",
"scripts",
"notebooks",
"training",
"corpus",
]
CACHES = [
Path.home() / ".torch",
Path.home() / ".caches" / "torch",
os.environ.get("TORCH_HOME"),
Path.home() / ".keras",
]
DVC_CONFIG_COMMENT = """# This file is auto-generated by spaCy based on your project.yml. Do not edit
# it directly and edit the project.yml instead and re-run the project."""
CLI_HELP = f"""Command-line interface for spaCy projects and working with project
templates. You'd typically start by cloning a project template to a local
directory and fetching its assets like datasets etc. See the project's
{CONFIG_FILE} for the available commands. Under the hood, spaCy uses DVC (Data
Version Control) to manage input and output files and to ensure steps are only
re-run if their inputs change.
"""
project_cli = typer.Typer(help=CLI_HELP)
@project_cli.callback(invoke_without_command=True)
def callback(ctx: typer.Context):
"""This runs before every project command and ensures DVC is installed."""
ensure_dvc()
################
# CLI COMMANDS #
################
@project_cli.command("clone")
def project_clone_cli(
# fmt: off
name: str = Arg(..., help="The name of the template to fetch"),
dest: Path = Arg(Path.cwd(), help="Where to download and work. Defaults to current working directory.", exists=False),
repo: str = Opt(about.__projects__, "--repo", "-r", help="The repository to look in."),
git: bool = Opt(False, "--git", "-G", help="Initialize project as a Git repo"),
no_init: bool = Opt(False, "--no-init", "-NI", help="Don't initialize the project with DVC"),
# fmt: on
):
"""Clone a project template from a repository. Calls into "git" and will
only download the files from the given subdirectory. The GitHub repo
defaults to the official spaCy template repo, but can be customized
(including using a private repo). Setting the --git flag will also
initialize the project directory as a Git repo. If the project is intended
to be a Git repo, it should be initialized with Git first, before
initializing DVC (Data Version Control). This allows DVC to integrate with
Git.
"""
project_clone(name, dest, repo=repo, git=git, no_init=no_init)
@project_cli.command("init")
def project_init_cli(
path: Path = Arg(..., help="Path to cloned project", exists=True, file_okay=False),
git: bool = Opt(False, "--git", "-G", help="Initialize project as a Git repo"),
):
"""Initialize a project directory with DVC and optionally Git. This should
typically be taken care of automatically when you run the "project clone"
command, but you can also run it separately. If the project is intended to
be a Git repo, it should be initialized with Git first, before initializing
DVC. This allows DVC to integrate with Git.
"""
project_init(path, git=git, silent=True)
@project_cli.command("assets")
def project_assets_cli(
# fmt: off
project_dir: Path = Arg(..., help="Path to cloned project", exists=True, file_okay=False),
# fmt: on
):
"""Use DVC (Data Version Control) to fetch project assets. Assets are
defined in the "assets" section of the project config. If possible, DVC
will try to track the files so you can pull changes from upstream. It will
also try and store the checksum so the assets are versioned. If th file
can't be tracked or checked, it will be downloaded without DVC. If a checksum
is provided in the project config, the file is only downloaded if no local
file with the same checksum exists.
"""
project_assets(project_dir)
@project_cli.command(
"run-all",
context_settings={"allow_extra_args": True, "ignore_unknown_options": True},
)
def project_run_all_cli(
# fmt: off
ctx: typer.Context,
project_dir: Path = Arg(..., help="Location of project directory", exists=True, file_okay=False),
show_help: bool = Opt(False, "--help", help="Show help message and available subcommands")
# fmt: on
):
"""Run all commands defined in the project. This command will use DVC and
the defined outputs and dependencies in the project config to determine
which steps need to be re-run and where to start. This means you're only
re-generating data if the inputs have changed.
This command calls into "dvc repro" and all additional arguments are passed
to the "dvc repro" command: https://dvc.org/doc/command-reference/repro
"""
if show_help:
print_run_help(project_dir)
else:
project_run_all(project_dir, *ctx.args)
@project_cli.command(
"run", context_settings={"allow_extra_args": True, "ignore_unknown_options": True},
)
def project_run_cli(
# fmt: off
ctx: typer.Context,
project_dir: Path = Arg(..., help="Location of project directory", exists=True, file_okay=False),
subcommand: str = Arg(None, help="Name of command defined in project config"),
show_help: bool = Opt(False, "--help", help="Show help message and available subcommands")
# fmt: on
):
"""Run a named script defined in the project config. If the command is
part of the default pipeline defined in the "run" section, DVC is used to
determine whether the step should re-run if its inputs have changed, or
whether everything is up to date. If the script is not part of the default
pipeline, it will be called separately without DVC.
If DVC is used, the command calls into "dvc repro" and all additional
arguments are passed to the "dvc repro" command:
https://dvc.org/doc/command-reference/repro
"""
if show_help or not subcommand:
print_run_help(project_dir, subcommand)
else:
project_run(project_dir, subcommand, *ctx.args)
@project_cli.command("exec", hidden=True)
def project_exec_cli(
# fmt: off
project_dir: Path = Arg(..., help="Location of project directory", exists=True, file_okay=False),
subcommand: str = Arg(..., help="Name of command defined in project config"),
# fmt: on
):
"""Execute a command defined in the project config. This CLI command is
only called internally in auto-generated DVC pipelines, as a shortcut for
multi-step commands in the project config. You typically shouldn't have to
call it yourself. To run a command, call "run" or "run-all".
"""
project_exec(project_dir, subcommand)
@project_cli.command("update-dvc")
def project_update_dvc_cli(
# fmt: off
project_dir: Path = Arg(..., help="Location of project directory", exists=True, file_okay=False),
verbose: bool = Opt(False, "--verbose", "-V", help="Print more info"),
force: bool = Opt(False, "--force", "-F", help="Force update DVC config"),
# fmt: on
):
"""Update the auto-generated DVC config file. Uses the steps defined in the
"run" section of the project config. This typically happens automatically
when running a command, but can also be triggered manually if needed.
"""
config = load_project_config(project_dir)
updated = update_dvc_config(project_dir, config, verbose=verbose, force=force)
if updated:
msg.good(f"Updated DVC config from {CONFIG_FILE}")
else:
msg.info(f"No changes found in {CONFIG_FILE}, no update needed")
app.add_typer(project_cli, name="project")
#################
# CLI FUNCTIONS #
#################
def project_clone(
name: str,
dest: Path,
*,
repo: str = about.__projects__,
git: bool = False,
no_init: bool = False,
) -> None:
"""Clone a project template from a repository.
name (str): Name of subdirectory to clone.
dest (Path): Destination path of cloned project.
repo (str): URL of Git repo containing project templates.
git (bool): Initialize project as Git repo. Should be set to True if project
is intended as a repo, since it will allow DVC to integrate with Git.
no_init (bool): Don't initialize DVC and Git automatically. If True, the
"init" command or "git init" and "dvc init" need to be run manually.
"""
dest = ensure_path(dest)
check_clone(name, dest, repo)
project_dir = dest.resolve()
# We're using Git and sparse checkout to only clone the files we need
with make_tempdir() as tmp_dir:
cmd = f"git clone {repo} {tmp_dir} --no-checkout --depth 1 --config core.sparseCheckout=true"
run_command(shlex.split(cmd))
with (tmp_dir / ".git" / "info" / "sparse-checkout").open("w") as f:
f.write(name)
run_command(["git", "-C", tmp_dir, "fetch"])
run_command(["git", "-C", tmp_dir, "checkout"])
shutil.move(str(tmp_dir / Path(name).name), str(project_dir))
msg.good(f"Cloned project '{name}' from {repo}")
for sub_dir in DIRS:
dir_path = project_dir / sub_dir
if not dir_path.exists():
dir_path.mkdir(parents=True)
if not no_init:
project_init(project_dir, git=git, silent=True)
msg.good(f"Your project is now ready!", dest)
print(f"To fetch the assets, run:\n{COMMAND} project assets {dest}")
def project_init(
project_dir: Path,
*,
git: bool = False,
silent: bool = False,
analytics: bool = False,
):
"""Initialize a project as a DVC and (optionally) as a Git repo.
project_dir (Path): Path to project directory.
git (bool): Also call "git init" to initialize directory as a Git repo.
silent (bool): Don't print any output (via DVC).
analytics (bool): Opt-in to DVC analytics (defaults to False).
"""
with working_dir(project_dir):
init_cmd = ["dvc", "init"]
if silent:
init_cmd.append("--quiet")
if not git:
init_cmd.append("--no-scm")
if git:
run_command(["git", "init"])
run_command(init_cmd)
# We don't want to have analytics on by default our users should
# opt-in explicitly. If they want it, they can always enable it.
if not analytics:
run_command(["dvc", "config", "core.analytics", "false"])
config = load_project_config(project_dir)
setup_check_dvc(project_dir, config)
def project_assets(project_dir: Path) -> None:
"""Fetch assets for a project using DVC if possible.
project_dir (Path): Path to project directory.
"""
project_path = ensure_path(project_dir)
config = load_project_config(project_path)
setup_check_dvc(project_path, config)
assets = config.get("assets", {})
if not assets:
msg.warn(f"No assets specified in {CONFIG_FILE}", exits=0)
msg.info(f"Fetching {len(assets)} asset(s)")
variables = config.get("variables", {})
for asset in assets:
url = asset["url"].format(**variables)
dest = asset["dest"].format(**variables)
fetch_asset(project_path, url, dest, asset.get("checksum"))
def fetch_asset(
project_path: Path, url: str, dest: Path, checksum: Optional[str] = None
) -> None:
"""Fetch an asset from a given URL or path. Will try to import the file
using DVC's import-url if possible (fully tracked and versioned) and falls
back to get-url (versioned) and a non-DVC download if necessary. If a
checksum is provided and a local file exists, it's only re-downloaded if the
checksum doesn't match.
project_path (Path): Path to project directory.
url (str): URL or path to asset.
checksum (Optional[str]): Optional expected checksum of local file.
"""
url = convert_asset_url(url)
dest_path = (project_path / dest).resolve()
if dest_path.exists() and checksum:
# If there's already a file, check for checksum
# TODO: add support for caches (dvc import-url with local path)
if checksum == get_checksum(dest_path):
msg.good(f"Skipping download with matching checksum: {dest}")
return
dvc_add_cmd = ["dvc", "add", str(dest_path), "--external"]
with working_dir(project_path):
try:
# If these fail, we don't want to output an error or info message.
# Try with tracking the source first, then just downloading with
# DVC, then a regular non-DVC download.
try:
dvc_cmd = ["dvc", "import-url", url, str(dest_path)]
print(subprocess.check_output(dvc_cmd, stderr=subprocess.DEVNULL))
except subprocess.CalledProcessError:
dvc_cmd = ["dvc", "get-url", url, str(dest_path)]
print(subprocess.check_output(dvc_cmd, stderr=subprocess.DEVNULL))
run_command(dvc_add_cmd)
except subprocess.CalledProcessError:
try:
download_file(url, dest_path)
except requests.exceptions.HTTPError as e:
msg.fail(f"Download failed: {dest}", e)
run_command(dvc_add_cmd)
if checksum and checksum != get_checksum(dest_path):
msg.warn(f"Checksum doesn't match value defined in {CONFIG_FILE}: {dest}")
msg.good(f"Fetched asset {dest}")
def project_run_all(project_dir: Path, *dvc_args) -> None:
"""Run all commands defined in the project using DVC.
project_dir (Path): Path to project directory.
*dvc_args: Other arguments passed to "dvc repro".
"""
config = load_project_config(project_dir)
setup_check_dvc(project_dir, config)
dvc_cmd = ["dvc", "repro", *dvc_args]
with working_dir(project_dir):
run_command(dvc_cmd)
def print_run_help(project_dir: Path, subcommand: Optional[str] = None) -> None:
"""Simulate a CLI help prompt using the info available in the project config.
project_dir (Path): The project directory.
subcommand (Optional[str]): The subcommand or None. If a subcommand is
provided, the subcommand help is shown. Otherwise, the top-level help
and a list of available commands is printed.
"""
config = load_project_config(project_dir)
setup_check_dvc(project_dir, config)
config_commands = config.get("commands", [])
commands = {cmd["name"]: cmd for cmd in config_commands}
if subcommand:
if subcommand not in commands:
msg.fail(f"Can't find command '{subcommand}' in project config", exits=1)
print(f"Usage: {COMMAND} project run {project_dir} {subcommand}")
help_text = commands[subcommand].get("help")
if help_text:
msg.text(f"\n{help_text}\n")
else:
print(f"\nAvailable commands in {CONFIG_FILE}")
print(f"Usage: {COMMAND} project run {project_dir} [COMMAND]")
msg.table([(cmd["name"], cmd.get("help", "")) for cmd in config_commands])
msg.text("Run all commands defined in the 'run' block of the project config:")
print(f"{COMMAND} project run-all {project_dir}")
def project_run(project_dir: Path, subcommand: str, *dvc_args) -> None:
"""Run a named script defined in the project config. If the script is part
of the default pipeline (defined in the "run" section), DVC is used to
execute the command, so it can determine whether to rerun it. It then
calls into "exec" to execute it.
project_dir (Path): Path to project directory.
subcommand (str): Name of command to run.
*dvc_args: Other arguments passed to "dvc repro".
"""
config = load_project_config(project_dir)
setup_check_dvc(project_dir, config)
config_commands = config.get("commands", [])
variables = config.get("variables", {})
commands = {cmd["name"]: cmd for cmd in config_commands}
if subcommand not in commands:
msg.fail(f"Can't find command '{subcommand}' in project config", exits=1)
if subcommand in config.get("run", []):
# This is one of the pipeline commands tracked in DVC
dvc_cmd = ["dvc", "repro", subcommand, *dvc_args]
with working_dir(project_dir):
run_command(dvc_cmd)
else:
cmd = commands[subcommand]
# Deps in non-DVC commands aren't tracked, but if they're defined,
# make sure they exist before running the command
for dep in cmd.get("deps", []):
if not (project_dir / dep).exists():
err = f"Missing dependency specified by command '{subcommand}': {dep}"
msg.fail(err, exits=1)
with working_dir(project_dir):
run_commands(cmd["script"], variables)
def project_exec(project_dir: Path, subcommand: str):
"""Execute a command defined in the project config.
project_dir (Path): Path to project directory.
subcommand (str): Name of command to run.
"""
config = load_project_config(project_dir)
config_commands = config.get("commands", [])
variables = config.get("variables", {})
commands = {cmd["name"]: cmd for cmd in config_commands}
with working_dir(project_dir):
run_commands(commands[subcommand]["script"], variables)
###########
# HELPERS #
###########
def load_project_config(path: Path) -> Dict[str, Any]:
"""Load the project config file from a directory and validate it.
path (Path): The path to the project directory.
RETURNS (Dict[str, Any]): The loaded project config.
"""
config_path = path / CONFIG_FILE
if not config_path.exists():
msg.fail("Can't find project config", config_path, exits=1)
config = srsly.read_yaml(config_path)
errors = validate(ProjectConfigSchema, config)
if errors:
msg.fail(f"Invalid project config in {CONFIG_FILE}", "\n".join(errors), exits=1)
return config
def update_dvc_config(
path: Path,
config: Dict[str, Any],
verbose: bool = False,
silent: bool = False,
force: bool = False,
) -> bool:
"""Re-run the DVC commands in dry mode and update dvc.yaml file in the
project directory. The file is auto-generated based on the config. The
first line of the auto-generated file specifies the hash of the config
dict, so if any of the config values change, the DVC config is regenerated.
path (Path): The path to the project directory.
config (Dict[str, Any]): The loaded project config.
verbose (bool): Whether to print additional info (via DVC).
silent (bool): Don't output anything (via DVC).
force (bool): Force update, even if hashes match.
RETURNS (bool): Whether the DVC config file was updated.
"""
config_hash = get_hash(config)
path = path.resolve()
dvc_config_path = path / DVC_CONFIG
if dvc_config_path.exists():
# Cneck if the file was generated using the current config, if not, redo
with dvc_config_path.open("r", encoding="utf8") as f:
ref_hash = f.readline().strip().replace("# ", "")
if ref_hash == config_hash and not force:
return False # Nothing has changed in project config, don't need to update
dvc_config_path.unlink()
variables = config.get("variables", {})
commands = []
# We only want to include commands that are part of the main list of "run"
# commands in project.yml and should be run in sequence
config_commands = {cmd["name"]: cmd for cmd in config.get("commands", [])}
for name in config.get("run", []):
if name not in config_commands:
msg.fail(f"Can't find command '{name}' in project config", exits=1)
command = config_commands[name]
deps = command.get("deps", [])
outputs = command.get("outputs", [])
outputs_no_cache = command.get("outputs_no_cache", [])
if not deps and not outputs and not outputs_no_cache:
continue
# Default to "." as the project path since dvc.yaml is auto-generated
# and we don't want arbitrary paths in there
project_cmd = ["python", "-m", NAME, "project", "exec", ".", name]
deps_cmd = [c for cl in [["-d", p] for p in deps] for c in cl]
outputs_cmd = [c for cl in [["-o", p] for p in outputs] for c in cl]
outputs_nc_cmd = [c for cl in [["-O", p] for p in outputs_no_cache] for c in cl]
dvc_cmd = ["dvc", "run", "-n", name, "-w", str(path), "--no-exec"]
if verbose:
dvc_cmd.append("--verbose")
if silent:
dvc_cmd.append("--quiet")
full_cmd = [*dvc_cmd, *deps_cmd, *outputs_cmd, *outputs_nc_cmd, *project_cmd]
commands.append(" ".join(full_cmd))
with working_dir(path):
run_commands(commands, variables, silent=True)
with dvc_config_path.open("r+", encoding="utf8") as f:
content = f.read()
f.seek(0, 0)
f.write(f"# {config_hash}\n{DVC_CONFIG_COMMENT}\n{content}")
return True
def ensure_dvc() -> None:
"""Ensure that the "dvc" command is available and show an error if not."""
try:
subprocess.run(["dvc", "--version"], stdout=subprocess.DEVNULL)
except Exception:
msg.fail(
"spaCy projects require DVC (Data Version Control) and the 'dvc' command",
"You can install the Python package from pip (pip install dvc) or "
"conda (conda install -c conda-forge dvc). For more details, see the "
"documentation: https://dvc.org/doc/install",
exits=1,
)
def setup_check_dvc(project_dir: Path, config: Dict[str, Any]) -> None:
"""Check that the project is set up correctly with DVC and update its
config if needed. Will raise an error if the project is not an initialized
DVC project.
project_dir (Path): The path to the project directory.
config (Dict[str, Any]): The loaded project config.
"""
if not project_dir.exists():
msg.fail(f"Can't find project directory: {project_dir}")
if not (project_dir / ".dvc").exists():
msg.fail(
"Project not initialized as a DVC project.",
f"Make sure that the project template was cloned correctly. To "
f"initialize the project directory manually, you can run: "
f"{COMMAND} project init {project_dir}",
exits=1,
)
with msg.loading("Updating DVC config..."):
updated = update_dvc_config(project_dir, config, silent=True)
if updated:
msg.good(f"Updated DVC config from changed {CONFIG_FILE}")
def run_commands(
commands: List[str] = tuple(), variables: Dict[str, str] = {}, silent: bool = False
) -> None:
"""Run a sequence of commands in a subprocess, in order.
commands (List[str]): The split commands.
variables (Dict[str, str]): Dictionary of variable names, mapped to their
values. Will be used to substitute format string variables in the
commands.
silent (boll): Don't print the commands.
"""
for command in commands:
# Substitute variables, e.g. "./{NAME}.json"
command = command.format(**variables)
command = shlex.split(command)
# TODO: is this needed / a good idea?
if len(command) and command[0] == "python":
command[0] = sys.executable
elif len(command) and command[0] == "pip":
command = [sys.executable, "-m", "pip", *command[1:]]
if not silent:
print(" ".join(command))
run_command(command)
def convert_asset_url(url: str) -> str:
"""Check and convert the asset URL if needed.
url (str): The asset URL.
RETURNS (str): The converted URL.
"""
# If the asset URL is a regular GitHub URL it's likely a mistake
if re.match("(http(s?)):\/\/github.com", url):
converted = url.replace("github.com", "raw.githubusercontent.com")
converted = re.sub(r"/(tree|blob)/", "/", converted)
msg.warn(
"Downloading from a regular GitHub URL. This will only download "
"the source of the page, not the actual file. Converting the URL "
"to a raw URL.",
converted,
)
return converted
return url
def check_clone(name: str, dest: Path, repo: str) -> None:
"""Check and validate that the destination path can be used to clone. Will
check that Git is available and that the destination path is suitable.
name (str): Name of the directory to clone from the repo.
dest (Path): Local destination of cloned directory.
repo (str): URL of the repo to clone from.
"""
try:
subprocess.run(["git", "--version"], stdout=subprocess.DEVNULL)
except Exception:
msg.fail(
f"Cloning spaCy project templates requires Git and the 'git' command. ",
f"To clone a project without Git, copy the files from the '{name}' "
f"directory in the {repo} to {dest} manually and then run:",
f"{COMMAND} project init {dest}",
exits=1,
)
if not dest:
msg.fail(f"Not a valid directory to clone project: {dest}", exits=1)
if dest.exists():
# Directory already exists (not allowed, clone needs to create it)
msg.fail(f"Can't clone project, directory already exists: {dest}", exits=1)
if not dest.parent.exists():
# We're not creating parents, parent dir should exist
msg.fail(
f"Can't clone project, parent directory doesn't exist: {dest.parent}",
exits=1,
)
def download_file(url: str, dest: Path, chunk_size: int = 1024) -> None:
"""Download a file using requests.
url (str): The URL of the file.
dest (Path): The destination path.
chunk_size (int): The size of chunks to read/write.
"""
response = requests.get(url, stream=True)
response.raise_for_status()
total = int(response.headers.get("content-length", 0))
progress_settings = {
"total": total,
"unit": "iB",
"unit_scale": True,
"unit_divisor": chunk_size,
"leave": False,
}
with dest.open("wb") as f, tqdm.tqdm(**progress_settings) as bar:
for data in response.iter_content(chunk_size=chunk_size):
size = f.write(data)
bar.update(size)

View File

@ -220,8 +220,11 @@ class TrainingSchema(BaseModel):
class ProjectConfigAsset(BaseModel):
# fmt: off
dest: StrictStr = Field(..., title="Destination of downloaded asset")
url: StrictStr = Field(..., title="URL of asset")
checksum: str = Field(None, title="MD5 hash of file", regex=r"([a-fA-F\d]{32})")
# fmt: on
class ProjectConfigCommand(BaseModel):
@ -229,11 +232,15 @@ class ProjectConfigCommand(BaseModel):
name: StrictStr = Field(..., title="Name of command")
help: Optional[StrictStr] = Field(None, title="Command description")
script: List[StrictStr] = Field([], title="List of CLI commands to run, in order")
dvc_deps: List[StrictStr] = Field([], title="Data Version Control dependencies")
dvc_outputs: List[StrictStr] = Field([], title="Data Version Control outputs")
dvc_outputs_no_cache: List[StrictStr] = Field([], title="Data Version Control outputs (no cache)")
deps: List[StrictStr] = Field([], title="Data Version Control dependencies")
outputs: List[StrictStr] = Field([], title="Data Version Control outputs")
outputs_no_cache: List[StrictStr] = Field([], title="Data Version Control outputs (no cache)")
# fmt: on
class Config:
title = "A single named command specified in a project config"
extra = "forbid"
class ProjectConfigSchema(BaseModel):
# fmt: off

View File

@ -1,15 +1,14 @@
import numpy
import tempfile
import shutil
import contextlib
import srsly
from pathlib import Path
from spacy import Errors
from spacy.tokens import Doc, Span
from spacy.attrs import POS, TAG, HEAD, DEP, LEMMA, MORPH
from spacy.vocab import Vocab
from spacy.util import make_tempdir # noqa: F401
@contextlib.contextmanager
@ -19,13 +18,6 @@ def make_tempfile(mode="r"):
f.close()
@contextlib.contextmanager
def make_tempdir():
d = Path(tempfile.mkdtemp())
yield d
shutil.rmtree(str(d))
def get_doc(
vocab,
words=[],

View File

@ -19,6 +19,9 @@ from packaging.specifiers import SpecifierSet, InvalidSpecifier
from packaging.version import Version, InvalidVersion
import subprocess
from contextlib import contextmanager
import tempfile
import shutil
import hashlib
try:
@ -455,6 +458,37 @@ def working_dir(path: Union[str, Path]) -> None:
os.chdir(prev_cwd)
@contextmanager
def make_tempdir():
"""Execute a block in a temporary directory and remove the directory and
its contents at the end of the with block.
YIELDS (Path): The path of the temp directory.
"""
d = Path(tempfile.mkdtemp())
yield d
shutil.rmtree(str(d))
def get_hash(data) -> str:
"""Get the hash for a JSON-serializable object.
data: The data to hash.
RETURNS (str): The hash.
"""
data_str = srsly.json_dumps(data, sort_keys=True).encode("utf8")
return hashlib.md5(data_str).hexdigest()
def get_checksum(path: Union[Path, str]) -> str:
"""Get the checksum for a file given its file path.
path (Union[Path, str]): The file path.
RETURNS (str): The checksum.
"""
return hashlib.md5(Path(path).read_bytes()).hexdigest()
def is_in_jupyter():
"""Check if user is running spaCy from a Jupyter notebook by detecting the
IPython kernel. Mainly used for the displaCy visualizer.