%global _empty_manifest_terminate_build 0
Name:		python-gcp-storage-emulator
Version:	2022.6.11
Release:	1
Summary:	A stub emulator for the Google Cloud Storage API
License:	BSD License
URL:		https://github.com/oittaa/gcp-storage-emulator
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/d6/b0/100bdd201799c3872e2015504e5b67126449938d86d42cbab1ed41a4754a/gcp-storage-emulator-2022.6.11.tar.gz
BuildArch:	noarch

Requires:	python3-fs
Requires:	python3-google-crc32c

%description
## Installation
`pip install gcp-storage-emulator`
## CLI Usage
### Starting the emulator
Start the emulator with:
```bash
gcp-storage-emulator start
```
By default, the server will listen on `http://localhost:9023` and data is stored under `./.cloudstorage`. You can configure the folder using the env variables `STORAGE_BASE` (default `./`) and `STORAGE_DIR` (default `.cloudstorage`).
If you wish to run the emulator in a testing environment or if you don't want to persist any data, you can use the `--in-memory` parameter. For tests, you might want to consider starting up the server from your code (see the [Python APIs](#python-apis))
If you're using the Google client library (e.g. `google-cloud-storage` for Python) then you can set the `STORAGE_EMULATOR_HOST` environment variable to tell the library to connect to your emulator endpoint rather than the standard `https://storage.googleapis.com`, e.g.:
```bash
export STORAGE_EMULATOR_HOST=http://localhost:9023
```
### Wiping data
You can wipe the data by running
```bash
gcp-storage-emulator wipe
```
You can pass `--keep-buckets` to wipe the data while keeping the buckets.
#### Example
Use in-memory storage and automatically create default storage bucket `my-bucket`.
```bash
gcp-storage-emulator start --host=localhost --port=9023 --in-memory --default-bucket=my-bucket
```
## Python APIs
To start a server from your code you can do
```python
from gcp_storage_emulator.server import create_server
server = create_server("localhost", 9023, in_memory=False)
server.start()
# ........
server.stop()
```
You can wipe the data by calling `server.wipe()`
This can also be achieved (e.g. during tests) by hitting the `/wipe` HTTP endpoint
#### Example
```python
import os
from google.cloud import storage
from gcp_storage_emulator.server import create_server
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
# default_bucket parameter creates the bucket automatically
server = create_server(HOST, PORT, in_memory=True, default_bucket=BUCKET)
server.start()
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
blob = bucket.blob("blob2")
blob.upload_from_string("test2")
for blob in bucket.list_blobs():
    content = blob.download_as_bytes()
    print(f"Blob [{blob.name}]: {content}")
server.stop()
```
## Docker
Pull the Docker image.
```bash
docker pull oittaa/gcp-storage-emulator
```
Inside the container instance, the value of the `PORT` environment variable always reflects the port to which requests are sent. It defaults to `8080`. The directory used for the emulated storage is located under `/storage` in the container. In the following example the host's directory `$(pwd)/cloudstorage` will be bound to the emulated storage.
```bash
docker run -d \
  -e PORT=9023 \
  -p 9023:9023 \
  --name gcp-storage-emulator \
  -v "$(pwd)/cloudstorage":/storage \
  oittaa/gcp-storage-emulator
```
```python
import os
from google.cloud import exceptions, storage
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
try:
    bucket = client.create_bucket(BUCKET)
except exceptions.Conflict:
    bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
print(blob.download_as_bytes())
```

%package -n python3-gcp-storage-emulator
Summary:	A stub emulator for the Google Cloud Storage API
Provides:	python-gcp-storage-emulator
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-gcp-storage-emulator
## Installation
`pip install gcp-storage-emulator`
## CLI Usage
### Starting the emulator
Start the emulator with:
```bash
gcp-storage-emulator start
```
By default, the server will listen on `http://localhost:9023` and data is stored under `./.cloudstorage`. You can configure the folder using the env variables `STORAGE_BASE` (default `./`) and `STORAGE_DIR` (default `.cloudstorage`).
If you wish to run the emulator in a testing environment or if you don't want to persist any data, you can use the `--in-memory` parameter. For tests, you might want to consider starting up the server from your code (see the [Python APIs](#python-apis))
If you're using the Google client library (e.g. `google-cloud-storage` for Python) then you can set the `STORAGE_EMULATOR_HOST` environment variable to tell the library to connect to your emulator endpoint rather than the standard `https://storage.googleapis.com`, e.g.:
```bash
export STORAGE_EMULATOR_HOST=http://localhost:9023
```
### Wiping data
You can wipe the data by running
```bash
gcp-storage-emulator wipe
```
You can pass `--keep-buckets` to wipe the data while keeping the buckets.
#### Example
Use in-memory storage and automatically create default storage bucket `my-bucket`.
```bash
gcp-storage-emulator start --host=localhost --port=9023 --in-memory --default-bucket=my-bucket
```
## Python APIs
To start a server from your code you can do
```python
from gcp_storage_emulator.server import create_server
server = create_server("localhost", 9023, in_memory=False)
server.start()
# ........
server.stop()
```
You can wipe the data by calling `server.wipe()`
This can also be achieved (e.g. during tests) by hitting the `/wipe` HTTP endpoint
#### Example
```python
import os
from google.cloud import storage
from gcp_storage_emulator.server import create_server
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
# default_bucket parameter creates the bucket automatically
server = create_server(HOST, PORT, in_memory=True, default_bucket=BUCKET)
server.start()
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
blob = bucket.blob("blob2")
blob.upload_from_string("test2")
for blob in bucket.list_blobs():
    content = blob.download_as_bytes()
    print(f"Blob [{blob.name}]: {content}")
server.stop()
```
## Docker
Pull the Docker image.
```bash
docker pull oittaa/gcp-storage-emulator
```
Inside the container instance, the value of the `PORT` environment variable always reflects the port to which requests are sent. It defaults to `8080`. The directory used for the emulated storage is located under `/storage` in the container. In the following example the host's directory `$(pwd)/cloudstorage` will be bound to the emulated storage.
```bash
docker run -d \
  -e PORT=9023 \
  -p 9023:9023 \
  --name gcp-storage-emulator \
  -v "$(pwd)/cloudstorage":/storage \
  oittaa/gcp-storage-emulator
```
```python
import os
from google.cloud import exceptions, storage
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
try:
    bucket = client.create_bucket(BUCKET)
except exceptions.Conflict:
    bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
print(blob.download_as_bytes())
```

%package help
Summary:	Development documents and examples for gcp-storage-emulator
Provides:	python3-gcp-storage-emulator-doc
%description help
## Installation
`pip install gcp-storage-emulator`
## CLI Usage
### Starting the emulator
Start the emulator with:
```bash
gcp-storage-emulator start
```
By default, the server will listen on `http://localhost:9023` and data is stored under `./.cloudstorage`. You can configure the folder using the env variables `STORAGE_BASE` (default `./`) and `STORAGE_DIR` (default `.cloudstorage`).
If you wish to run the emulator in a testing environment or if you don't want to persist any data, you can use the `--in-memory` parameter. For tests, you might want to consider starting up the server from your code (see the [Python APIs](#python-apis))
If you're using the Google client library (e.g. `google-cloud-storage` for Python) then you can set the `STORAGE_EMULATOR_HOST` environment variable to tell the library to connect to your emulator endpoint rather than the standard `https://storage.googleapis.com`, e.g.:
```bash
export STORAGE_EMULATOR_HOST=http://localhost:9023
```
### Wiping data
You can wipe the data by running
```bash
gcp-storage-emulator wipe
```
You can pass `--keep-buckets` to wipe the data while keeping the buckets.
#### Example
Use in-memory storage and automatically create default storage bucket `my-bucket`.
```bash
gcp-storage-emulator start --host=localhost --port=9023 --in-memory --default-bucket=my-bucket
```
## Python APIs
To start a server from your code you can do
```python
from gcp_storage_emulator.server import create_server
server = create_server("localhost", 9023, in_memory=False)
server.start()
# ........
server.stop()
```
You can wipe the data by calling `server.wipe()`
This can also be achieved (e.g. during tests) by hitting the `/wipe` HTTP endpoint
#### Example
```python
import os
from google.cloud import storage
from gcp_storage_emulator.server import create_server
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
# default_bucket parameter creates the bucket automatically
server = create_server(HOST, PORT, in_memory=True, default_bucket=BUCKET)
server.start()
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
blob = bucket.blob("blob2")
blob.upload_from_string("test2")
for blob in bucket.list_blobs():
    content = blob.download_as_bytes()
    print(f"Blob [{blob.name}]: {content}")
server.stop()
```
## Docker
Pull the Docker image.
```bash
docker pull oittaa/gcp-storage-emulator
```
Inside the container instance, the value of the `PORT` environment variable always reflects the port to which requests are sent. It defaults to `8080`. The directory used for the emulated storage is located under `/storage` in the container. In the following example the host's directory `$(pwd)/cloudstorage` will be bound to the emulated storage.
```bash
docker run -d \
  -e PORT=9023 \
  -p 9023:9023 \
  --name gcp-storage-emulator \
  -v "$(pwd)/cloudstorage":/storage \
  oittaa/gcp-storage-emulator
```
```python
import os
from google.cloud import exceptions, storage
HOST = "localhost"
PORT = 9023
BUCKET = "test-bucket"
os.environ["STORAGE_EMULATOR_HOST"] = f"http://{HOST}:{PORT}"
client = storage.Client()
try:
    bucket = client.create_bucket(BUCKET)
except exceptions.Conflict:
    bucket = client.bucket(BUCKET)
blob = bucket.blob("blob1")
blob.upload_from_string("test1")
print(blob.download_as_bytes())
```

%prep
%autosetup -n gcp-storage-emulator-2022.6.11

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-gcp-storage-emulator -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2022.6.11-1
- Package Spec generated