Add unix details, and dependency versions

Author: Lyetenth

README.md

@@ -1,4 +1,4 @@
-# First Street Foundation API Access Documentation (Python)
+# First Street Foundation API Access Documentation (Python 3.6+)
 [![CircleCI](https://img.shields.io/circleci/build/gh/FirstStreet/fsf_api_access_python)](https://circleci.com/gh/FirstStreet/fsf_api_access_python)
 ![GitHub](https://img.shields.io/github/license/firststreet/fsf_api_access_python)
 
@@ -49,10 +49,11 @@ Current release: 0.1
 
     ![Screenshot](doc/images/1.2.3.png)
 
-3. Open `git bash` and create then navigate to a new project directory
+3. Open `git bash` or a `bash terminal` (if on a MacOS or Linux) and create then navigate to a new project directory
 
     ```sh
     mkdir fsf_api
+   
     cd fsf_api
     ```
 
@@ -74,7 +75,7 @@ Current release: 0.1
 
     ![Screenshot](doc/images/1.3.1.png)
 
-5. [Optional] Open a new console or close and re-open a console and create and activate a new virtual environment in the project directory:
+5. [Optional] Open a new `powershell console` / `bash terminal` or close and re-open a console and create and activate a new virtual environment in the project directory:
     ```sh
     python -m venv /path/to/new/virtual/environment
    
@@ -111,15 +112,24 @@ Current release: 0.1
 ## [Running the Project - Method 1: Through the Command Line](#toc)
 **[Reminder] Keep your API key safe, and do not share it with others!**
 
-1. [Required] Set an Environmental Variable with the `variable_name` as `FSF_API_KEY` and the `variable_value` with the `API_KEY`.
+[NOTE] This method will always generate a CSV. 
+
+1.  ## **MacOS or Linux** 
+    [Required] Open a `bash terminal` and set an Environmental Variable with the `variable_name` as `FSF_API_KEY` and the `variable_value` with the `API_KEY` with the command
+    ```shell script
+    export FSF_API_KEY=your personal API key
+    ``` 
+    
+    ## **Windows** 
+    [Required] Set an Environmental Variable with the `variable_name` as `FSF_API_KEY` and the `variable_value` with the `API_KEY`.
 
     ![Screenshot](doc/images/3.1.1.png)
 
     ![Screenshot](doc/images/3.1.2.png)
 
     ![Screenshot](doc/images/3.1.3.png)
 
-2. Open a new console and navigate to the project directory. Next, call one of the methods described below in the `Products` section through the command line. See the `Examples` section for more examples.
+2. Open/Re-open a `powershell console` / `bash terminal` and navigate to the project directory. Next, call one of the methods described below in the `Products` section through the command line. See the `Examples` section for more examples.
     ```sh
     cd /path/to/project
     python -m firststreet -p <product>.<product_subtype> -i <fsids> -f <file_name> -l <lookup_type>
@@ -180,6 +190,8 @@ Current release: 0.1
 ## [Running the Project - Method 2: Through the Client](#toc)
 **[Reminder] Keep your API key safe, and do not share it with others!**
 
+[NOTE] This method will **NOT** generate a CSV by default. An argument must be passed to generate a CSV.
+
 1. Create a new Python script (by using notepad or any other text editor) and initialize a First Street Foundation API Client. 
     ```python
     # Contents of my_script.py
@@ -218,6 +230,9 @@ Current release: 0.1
 
 <a name="products"></a>
 # [Products](#toc)
+
+**NOTE**: As of the current release, only direct FSID lookups are available through this wrapper. Lat/lng and address query will be in a later release
+
 <a name="location"></a>
 #### [Location](#toc)
 
@@ -444,7 +459,7 @@ If an update is made to this project, you will need to pull the changes from git
 
     ![Screenshot](doc/images/6.1.1.png)
 
-2. Open a new console, navigate to the project, and re-run the setup script to re-install the project:
+2. Open a new `powershell console` / `bash terminal`, navigate to the project, and re-run the setup script to re-install the project:
 
     ```shell script
     cd /path/to/project

firststreet/api/api.py

@@ -38,8 +38,8 @@ def call_api(self, fsids, product, product_subtype, location, limit=100):
         """
         if not isinstance(fsids, list):
             if isinstance(fsids, str):
-                if os.path.isfile(os.getcwd() + "\\" + fsids):
-                    fsids = read_fsid_file(os.getcwd() + "\\" + fsids)
+                if os.path.isfile(os.getcwd() + "console/terminal" + fsids):
+                    fsids = read_fsid_file(os.getcwd() + "/" + fsids)
                 else:
                     raise InvalidArgument("File provided is not a valid file. "
                                           "Please check the file name. '{}'".format(os.path.curdir + str(fsids)))

firststreet/api/csv_format.py

@@ -3,6 +3,7 @@
 
 # Standard Imports
 import datetime
+import logging
 import os
 
 # External Imports
@@ -29,7 +30,7 @@ def to_csv(data, product, product_subtype, location_type=None, output_dir=None):
         file_name = "_".join([date, product, product_subtype]) + ".csv"
 
     if not output_dir:
-        output_dir = os.getcwd() + "\\data_csv"
+        output_dir = os.getcwd() + "/data_csv"
 
     if not os.path.exists(output_dir):
         os.makedirs(output_dir)
@@ -137,6 +138,7 @@ def to_csv(data, product, product_subtype, location_type=None, output_dir=None):
     # Export CSVs
     df.fillna(pd.NA, inplace=True)
     df.to_csv(output_dir + '/' + file_name, index=False)
+    logging.info("CSV generated to '{}'.".format(output_dir + '/' + file_name))
 
 
 def format_adaptation_detail(data):

requirements.txt

@@ -1,4 +1,4 @@
-aiohttp
-shapely
-pandas
-tqdm
+aiohttp >= 3.6.2
+shapely >= 1.7.0
+pandas >= 1.0.5
+tqdm >= 4.46.1

tests/temp/test_full02020_06_25_12_40_03_adaptation_detail.csv

@@ -28,6 +28,7 @@ def test_full(tmpdir):
     fs.probability.get_count([39047], 'county', csv=True, output_dir=tmpdir)
     fs.probability.get_count([3904], 'cd', csv=True, output_dir=tmpdir)
     fs.probability.get_count([39], 'state', csv=True, output_dir=tmpdir)
+    fs.probability.get_count_summary([394406220], csv=True, output_dir=tmpdir)
     fs.probability.get_cumulative([390000439], csv=True, output_dir=tmpdir)
     fs.probability.get_depth([390000227], csv=True, output_dir=tmpdir)
     fs.environmental.get_precipitation([39057], csv=True, output_dir=tmpdir)