diff --git a/README.md b/README.md
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+# FuzzyMap <img src="https://avatars.githubusercontent.com/u/108220139" align="right" height="64" />
+
+[![PyPI](https://img.shields.io/pypi/v/fuzzymap.svg)](https://pypi.org/project/fuzzymap/)
+[![License](https://img.shields.io/pypi/l/fuzzymap.svg)](https://github.com/pysnippet/fuzzymap/blob/master/LICENSE)
+
+## What is FuzzyMap?
+
+`FuzzyMap` is a polymorph Python dictionary. This kind of dictionary returns the value of the exact key if there is such
+a key. Otherwise, it will return the value of the most similar key satisfying the given ratio. The same mechanism works
+when setting a new or replacing an old key in the dictionary. If the key is not found and does not match any of the keys
+by the given ratio, it returns `None`.
+
+## How does it work?
+
+Suppose you have scraped data from multiple sources that do not have a unique identifier, and you want to compare the
+values of the items having the same identifiers. Sure there will be found a field that mostly has an equivalent value
+at each source. And you can use that field to identify the corresponding items of other sources' data.
+
+## Let's look at the following example
+
+There is a live data parser that collects the coefficients of football matches from different bookmakers at once, then
+calculates and logs the existing forks. Many bookmakers change the name of the teams to be incomparable with names on
+other sites.
+
+```python
+from fuzzymap import FuzzyMap
+
+src1 = {
+    'Rapid Wien - First Vienna': {'w1': 1.93, 'x': 2.32, 'w2': 7.44},
+    'Al Bourj - Al Nejmeh': {'w1': 26, 'x': 11.5, 'w2': 1.05},
+    # hundreds of other teams' data
+}
+
+src2 = FuzzyMap({
+    'Bourj FC - Nejmeh SC Beirut': {'w1': 32, 'x': 12, 'w2': 1.05},
+    'SK Rapid Wien - First Vienna FC': {'w1': 1.97, 'x': 2.3, 'w2': 8.2},
+    # hundreds of other teams' data
+})
+
+for team, coefs1 in src1.items():
+    coefs2 = src2[team]
+
+    # coefs1 = {"w1": 1.93, "x": 2.32, "w2": 7.44}
+    # coefs2 = {"w1": 1.97, "x": 2.3, "w2": 8.2}
+    handle_fork(coefs1, coefs2)
+```
+
+With a human brain, it is not difficult to identify that "Rapid Wien - First Vienna" and "SK Rapid Wien - First Vienna
+FC" matches are the same. In the above example, the `src2` is defined as `FuzzyMap`, it makes its keys fuzzy-matchable,
+and we can get an item corresponding to the key of `src1`. See the below graph demonstrating the associations of
+`FuzzyMap` keys.
+
+```mermaid
+graph LR
+    src1team1[Rapid Wien - First Vienna]-->src1coefs1["{'w1': 1.93, 'x': 2.32, 'w2': 7.44}"]
+    src1team2[Al Bourj - Al Nejmeh]-->src1coefs2["{'w1': 26, 'x': 11.5, 'w2': 1.05}"]
+    src2team1[SK Rapid Wien - First Vienna FC]-->src2coefs1["{'w1': 1.97, 'x': 2.3, 'w2': 8.2}"]
+    src2team2[Bourj FC - Nejmeh SC Beirut]-->src2coefs2["{'w1': 32, 'x': 12, 'w2': 1.05}"]
+    src1team1-->src2coefs1
+    src1team2-->src2coefs2
+```
+
+## License
+
+Copyright (C) 2022 Artyom Vancyan. [GPLv2](LICENSE)
diff --git a/setup.py b/setup.py
index f8ef21b..1b00861 100644
--- a/setup.py
+++ b/setup.py
@@ -29,7 +29,7 @@
     version=version,
     author="Artyom Vancyan",
     author_email="artyom@pysnippet.org",
-    # description="",
+    description="Python dictionary with a FUZZY key-matching opportunity",
     # long_description=long_description,
     # long_description_content_type="text/markdown",
     url="https://github.com/pysnippet/fuzzymap",