Metadata-Version: 2.1
Name: data-downloader
Version: 0.2.4
Summary: Make downloading scientific data much easier
Home-page: https://github.com/Fanchengyan/data-downloader
Author: fanchegyan
Author-email: fanchy14@lzu.edu.cn
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: httpx (>=0.14.0)
Requires-Dist: tqdm
Requires-Dist: setuptools
Requires-Dist: beautifulsoup4
Requires-Dist: nest-asyncio
Requires-Dist: python-dateutil

# data-downloader

Make downloading scientific data much easier

## Introduction

data-downloader is a very convenient and powerful data download package for retrieving files using HTTP, HTTPS. It current includes download model `downloader` and url parsing model `parse_urls`. As `httpx` was used which provided a method to access website with synchronous and asynchronous way, you can download multiple files at the same time.

data-downloader has many features to make retrieving files easy, including:

- Can resume aborted downloads automatically when you re-execute the code if website support resuming (status code is 216 or 416 when send a HEAD request to the server supplying a Range header)
- Can download multiple files at the same time when download a single file very slow. There are two methods provided to achieve this function：
  - `async_download_datas` (recommend) function could download mare than 100 files at the same time as using asynchronous requests of `httpx`
  - `mp_download_datas` function depends on your CPU of computer as using `multiprocessing` package
- Provide a convenient way to manage your username and password in `.netrc` file. When the website requires the username and password, there is no need to provide it every time you download
- Provide a convenient way to parse urls. 
  - `from_urls_file` : parse urls of data from a file which only contains urls 
  - `from_sentinel_meta4` : parse urls from sentinel `products.meta4` file downloaded from <https://scihub.copernicus.eu/dhus>
  - `from_EarthExplorer_order` : parse urls from orders in EarthExplorer (same as `bulk-downloader`)
  - `from_html` : parse urls from html website


## 1. Installation

It is recommended to use the latest version of pip to install **data_downloader**.

``` BASH
pip install data_downloader
```

## 2. downloader Usage

All downloading functions are in `data_downloader.downloader` . So import `downloader` at the beginning.

``` Python
from data_downloader import downloader
```

### 2.1 Netrc

If the website needs to log in, you can add a record to a `.netrc` file in your home which contains your login information to avoid supplying username and password each time you download data.

To view existing hosts in `.netrc` file:

``` Python
netrc = downloader.Netrc()
print(netrc.hosts)
```

To add a record

``` Python
netrc.add(self, host, login, password, account=None, overwrite=False)
```

If you want to update a record, set tha parameter `overwrite=True` 

for NASA data user:

``` Python
netrc.add('urs.earthdata.nasa.gov','your_username','your_password')
```

You can use the `downloader.get_url_host(url)` to get the host name when you don't know the host of the website:

``` python
host = downloader.get_url_host(url)
```

To remove a record

``` Python
netrc.remove(self, host)
```

To clear all records

``` Python
netrc.clear()
```

**Example:**

``` Python
In [2]: netrc = downloader.Netrc()
In [3]: netrc.hosts
Out[3]: {}

In [4]: netrc.add('urs.earthdata.nasa.gov','username','passwd') 

In [5]: netrc.hosts
Out[5]: {'urs.earthdata.nasa.gov': ('username', None, 'passwd')}

In [6]: netrc
Out[6]:
machine urs.earthdata.nasa.gov
	login username
	password passwd

# This command only for linux user
In [7]: !cat ~/.netrc
machine urs.earthdata.nasa.gov
	login username
	password passwd

In [8]: url = 'https://gpm1.gesdisc.eosdis.nasa.gov/daac-bin/OTF/HTTP_services.cgi?FILENAME=%2Fdata%2FGPM_L3%2FGPM_3IMERGM.06%2F2000%2F3B-MO.MS.MRG.3IMERG.20000601-S000000-E235959.06.V06B.HDF5&FORMAT=bmM0Lw&BBOX=31.904%2C99.492%2C35.771%2C105.908&LABEL=3B-MO.MS.MRG.3IMERG.20000601-S000000-E235959.06.V06B.HDF5.SUB.nc4&SHORTNAME=GPM_3IMERGM&SERVICE=L34RS_GPM&VERSION=1.02&DATASET_VERSION=06&VARIABLES=precipitation'

In [9]: downloader.get_url_host(url)
Out[9]: 'gpm1.gesdisc.eosdis.nasa.gov'

In [10]: netrc.add(downloader.get_url_host(url),'username','passwd')

In [11]: netrc
Out[11]:
machine urs.earthdata.nasa.gov
        login username
        password passwd
machine gpm1.gesdisc.eosdis.nasa.gov
        login username
        password passwd

In [12]: netrc.add(downloader.get_url_host(url),'username','new_passwd')
>>> Warning: test_host existed, nothing will be done. If you want to overwrite the existed record, set overwrite=True

In [13]: netrc
Out[13]:
machine urs.earthdata.nasa.gov
        login username
        password passwd
machine gpm1.gesdisc.eosdis.nasa.gov
        login username
        password passwd

In [14]: netrc.add(downloader.get_url_host(url),'username','new_passwd',overwrite=True)

In [15]: netrc
Out[15]:
machine urs.earthdata.nasa.gov
        login username
        password passwd
machine gpm1.gesdisc.eosdis.nasa.gov
        login username
        password new_passwd

In [16]: netrc.remove(downloader.get_url_host(url))

In [17]: netrc
Out[17]:
machine urs.earthdata.nasa.gov
        login username
        password passwd

In [18]: netrc.clear()

In [19]: netrc.hosts
Out[19]: {}
```

### 2.2 download_data

This function is design for downloading a single file. Try to use `download_datas`, `mp_download_datas` or `async_download_datas` function if you have a lot of files to download

``` Python
downloader.download_data(url, folder=None, file_name=None, client=None)
```

**Parameters:**

``` 
url: str
    url of web file
folder: str
    the folder to store output files. Default current folder. 
file_name: str
    the file name. If None, will parse from web response or url.
    file_name can be the absolute path if folder is None.
client: httpx.Client() object
    client maintaining connection. Default None
```

**Example:**

``` Python
In [6]: url = 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20141211/20141117_201
   ...: 41211.geo.unw.tif'
   ...:  
   ...: folder = 'D:\\data'
   ...: downloader.download_data(url,folder)

20141117_20141211.geo.unw.tif:   2%|▌                   | 455k/22.1M [00:52<42:59, 8.38kB/s]
```

### 2.3 download_datas

download datas from a list like object that contains urls. This function will download files one by one.

``` Python
downloader.download_datas(urls, folder=None, file_names=None):
```

**Parameters:**

``` 
urls:  iterator
    iterator contains urls
folder: str
    the folder to store output files. Default current folder.
file_names: iterator
    iterator contains names of files. Leaving it None if you want the program to parse 
    them from website. file_names can contain the absolute paths if folder is None.
```

**Examples:**

``` python
In [12]: from data_downloader import downloader 
    ...:  
    ...: urls=['http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20141211/20141117_20
    ...: 141211.geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150221/20141024_20150221
    ...: .geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150128/20141024_20150128
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150128/20141024_20150128
    ...: .geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141211_20150128/20141211_20150128
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20150317/20141117_20150317
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20150221/20141117_20150221
    ...: .geo.cc.tif']  
    ...:  
    ...: folder = 'D:\\data' 
    ...: downloader.download_datas(urls,folder)

20141117_20141211.geo.unw.tif:   6%|█           | 1.37M/22.1M [03:09<2:16:31, 2.53kB/s]
```

### 2.4 mp_download_datas
Download files simultaneously using multiprocessing. The website that don't support resuming may download incompletely. You can use `download_datas` instead

``` Python
downloader.mp_download_datas(urls, folder=None, file_names=None, ncore=None, desc='')
```


**Parameters:**

``` 
urls:  iterator
    iterator contains urls
folder: str
    the folder to store output files. Default current folder.
file_names: iterator
    iterator contains names of files. Leaving it None if you want the program to parse
    them from website. file_names can cantain the absolute paths if folder is None.
ncore: int
    Number of cores for parallel downloading. If ncore is None, then the number returned
    by os.cpu_count() is used. Default None.
desc: str
    description of datas downloading
```

**Example:**

```python
In [12]: from data_downloader import downloader 
    ...:  
    ...: urls=['http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20141211/20141117_20
    ...: 141211.geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150221/20141024_20150221
    ...: .geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150128/20141024_20150128
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141024_20150128/20141024_20150128
    ...: .geo.unw.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141211_20150128/20141211_20150128
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20150317/20141117_20150317
    ...: .geo.cc.tif', 
    ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_131313/interferograms/20141117_20150221/20141117_20150221
    ...: .geo.cc.tif']  
    ...:  
    ...: folder = 'D:\\data' 
    ...: downloader.mp_download_datas(urls,folder)

 >>> 12 parallel downloading
 >>> Total | :   0%|                                         | 0/7 [00:00<?, ?it/s]
20141211_20150128.geo.cc.tif:  15%|██▊                | 803k/5.44M [00:00<?, ?B/s]
```

### 2.5 async_download_datas

Download files simultaneously with asynchronous mode. The website that don't support resuming may lead to download incompletely. You can use `download_datas` instead

``` Python
downloader.async_download_datas(urls, folder=None, file_names=None, limit=30, desc='')
```

**Parameters:**

``` 
urls:  iterator
    iterator contains urls
folder: str 
    the folder to store output files. Default current folder.
file_names: iterator
    iterator contains names of files. Leaving it None if you want the program 
    to parse them from website. file_names can contain the absolute paths if folder is None.
limit: int
    the number of files downloading simultaneously
desc: str
    description of datas downloading
```

**Example:**

``` python
In [3]: from data_downloader import downloader 
   ...:  
   ...: urls=['http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049
   ...: _131313/interferograms/20141117_20141211/20141117_20141211.geo.unw.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141024_20150221/20141024_20150221.geo.unw.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141024_20150128/20141024_20150128.geo.cc.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141024_20150128/20141024_20150128.geo.unw.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141211_20150128/20141211_20150128.geo.cc.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141117_20150317/20141117_20150317.geo.cc.tif', 
   ...: 'http://gws-access.ceda.ac.uk/public/nceo_geohazards/LiCSAR_products/106/106D_05049_13131
   ...: 3/interferograms/20141117_20150221/20141117_20150221.geo.cc.tif']  
   ...:  
   ...: folder = 'D:\\data' 
   ...: downloader.async_download_datas(urls,folder,limit=3,desc='interferograms')

>>> Total | Interferograms :   0%|                          | 0/7 [00:00<?, ?it/s]
    20141024_20150221.geo.unw.tif:  11%|▌    | 2.41M/21.2M [00:11<41:44, 7.52kB/s]
    20141117_20141211.geo.unw.tif:   9%|▍    | 2.06M/22.1M [00:11<25:05, 13.3kB/s]
    20141024_20150128.geo.cc.tif:  36%|██▏   | 1.98M/5.42M [00:12<04:17, 13.4kB/s] 
    20141117_20150317.geo.cc.tif:   0%|               | 0.00/5.44M [00:00<?, ?B/s]
    20141117_20150221.geo.cc.tif:   0%|               | 0.00/5.47M [00:00<?, ?B/s]
    20141024_20150128.geo.unw.tif:   0%|              | 0.00/23.4M [00:00<?, ?B/s]
    20141211_20150128.geo.cc.tif:   0%|               | 0.00/5.44M [00:00<?, ?B/s]
```

### 2.6 status_ok

Simultaneously detecting whether the given links are accessible. 

``` Python
status_ok(urls, limit=200, timeout=60)
```

**Parameters**

``` 
urls: iterator
    iterator contains urls
limit: int
    the number of urls connecting simultaneously
timeout: int
    Request to stop waiting for a response after a given number of seconds
```

**Return:**

a list of results (True or False)

**Example:**

``` python
In [1]: from data_downloader import downloader
   ...: import numpy as np
   ...: 
   ...: urls = np.array(['https://www.baidu.com',
   ...: 'https://www.bai.com/wrongurl',
   ...: 'https://cn.bing.com/',
   ...: 'https://bing.com/wrongurl',
   ...: 'https://bing.com/'] )
   ...: 
   ...: status_ok = downloader.status_ok(urls)
   ...: urls_accessable = urls[status_ok]
   ...: print(urls_accessable)

['https://www.baidu.com' 'https://cn.bing.com/' 'https://bing.com/']
```
## 3. parse_url Usage

Provides a very simple way to get URLs from various medias

to import:
```python
from data_downloader import parse_urls
```

### 3.1 from_urls_file

parse urls from a file which only contains urls 

```python
parse_urls.from_urls_file(url_file)
```

**Parameters:**

    url_file: str
        path to file which only contains urls 

**Return:**

a list contains urls


### 3.2 from_sentinel_meta4

parse urls from sentinel `products.meta4` file downloaded from  <https://scihub.copernicus.eu/dhus>

```python
parse_urls.from_sentinel_meta4(url_file)
```

**Parameters:**

    url_file: str
        path to products.meta4

**Return:**

a list contains urls

### 3.3 from_html


parse urls from html website

```python
parse_urls.from_html(url, suffix=None, suffix_depth=0, url_depth=0)
```

**Parameters:**

    url: str
        the website contains datas
    suffix: list, optional
        data format. suffix should be a list contains multipart. 
        if suffix_depth is 0, all '.' will parsed. 
        Examples: 
            when set 'suffix_depth=0':
                suffix of 'xxx8.1_GLOBAL.nc' should be ['.1_GLOBAL', '.nc']
                suffix of 'xxx.tar.gz' should be ['.tar', '.gz']
            when set 'suffix_depth=1':
                suffix of 'xxx8.1_GLOBAL.nc' should be ['.nc']
                suffix of 'xxx.tar.gz' should be ['.gz']
    suffix_depth: integer
        Number of suffixes
    url_depth: integer
        depth of url in website will parsed

**Return:**

a list contains urls

**Example:**

```python
from downloader import parse_urls

url = 'https://cds-espri.ipsl.upmc.fr/espri/pubipsl/iasib_CH4_2014_uk.jsp'
urls = parse_urls.from_html(url, suffix=['.nc'], suffix_depth=1)
urls_all = parse_urls.from_html(url, suffix=['.nc'], suffix_depth=1, url_depth=1)
print(len(urls_all)-len(urls))
```

### 3.4 from_EarthExplorer_order

parse urls from orders in earthexplorer.

Reference: [bulk-downloader](https://code.usgs.gov/espa/bulk-downloader)


```python
parse_urls.from_EarthExplorer_order(username=None, passwd=None, email=None,
                                    order=None, url_host=None)
```

**Parameters:**

    username, passwd: str, optional
        your username and passwd to login in EarthExplorer. Chould be
        None when you have save them in .netrc
    email: str, optional
        email address for the user that submitted the order
    order: str or dict
        which order to download. If None, all orders retrieved from 
        EarthExplorer will be used.
    url_host: str
        if host is not USGS ESPA

**Return:**

a dict in format of {orderid: urls}

**Example:**

```python
from pathlib import Path
from data_downloader import downloader, parse_urls
folder_out = Path('D:\\data')
urls_info = parse_urls.from_EarthExplorer_order(
            'your username', 'your passwd')
for odr in urls_info.keys():
    folder = folder_out.joinpath(odr)
    if not folder.exists():
        folder.mkdir()
    urls = urls_info[odr]
    downloader.download_datas(urls, folder)
```

